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","language":"English","publisher":"University of Nebraska--Lincoln. Center for Great Plains Studies","publisherLocation":"Lincoln, NE","doi":"10.1353/gpr.2015.0018","usgsCitation":"Kinzel, P.J., Bauer, M., Feller, M.R., Holmquist-Johnson, C., and Preston, T., 2015, Experimental flights using a small unmanned aircraft system for mapping emergent sandbars: Great Plains Research, v. 25, no. 1, p. 39-52, https://doi.org/10.1353/gpr.2015.0018.","productDescription":"14 p.","startPage":"39","endPage":"52","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053315","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":320129,"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 -99.45064544677734,\n 40.68138655718806\n ],\n [\n -99.45064544677734,\n 40.68724434319262\n ],\n [\n -99.43382263183594,\n 40.68724434319262\n ],\n [\n -99.43382263183594,\n 40.68138655718806\n ],\n [\n -99.45064544677734,\n 40.68138655718806\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.55973625183105,\n 40.679759303041855\n ],\n [\n -99.55973625183105,\n 40.683990081194764\n ],\n [\n -99.54733371734619,\n 40.683990081194764\n ],\n [\n -99.54733371734619,\n 40.679759303041855\n ],\n [\n -99.55973625183105,\n 40.679759303041855\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57160536e4b0ef3b7ca91ff4","contributors":{"authors":[{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":626879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bauer, Mark A. mabauer@usgs.gov","contributorId":1409,"corporation":false,"usgs":true,"family":"Bauer","given":"Mark A.","email":"mabauer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":626880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feller, Mark R. mrfeller@usgs.gov","contributorId":3904,"corporation":false,"usgs":true,"family":"Feller","given":"Mark","email":"mrfeller@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":626881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holmquist-Johnson, Christopher 0000-0002-2782-7687 h-johnsonc@usgs.gov","orcid":"https://orcid.org/0000-0002-2782-7687","contributorId":168648,"corporation":false,"usgs":true,"family":"Holmquist-Johnson","given":"Christopher","email":"h-johnsonc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":626882,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Preston, Todd","contributorId":81379,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","affiliations":[],"preferred":false,"id":626883,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70140748,"text":"ds921 - 2015 - Ground-based lidar beach topography of Fire Island, New York, April 2013","interactions":[],"lastModifiedDate":"2017-08-14T11:25:35","indexId":"ds921","displayToPublicDate":"2015-03-02T09:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"921","title":"Ground-based lidar beach topography of Fire Island, New York, April 2013","docAbstract":"The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in Florida and the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina, collaborated to gather alongshore ground-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on April 10, 2013, to characterize beach topography following substantial erosion that occurred during Hurricane Sandy, which made landfall on October 29, 2012, and multiple, strong winter storms. The ongoing beach monitoring is part of the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds921","usgsCitation":"Brenner, O.T., Hapke, C.J., Spore, N.J., Brodie, K.L., and McNinch, J., 2015, Ground-based lidar beach topography of Fire Island, New York, April 2013: U.S. Geological Survey Data Series 921, HTML Document, https://doi.org/10.3133/ds921.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2013-04-01","temporalEnd":"2013-04-30","ipdsId":"IP-060922","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":298194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds921.jpg"},{"id":344813,"rank":7,"type":{"id":18,"text":"Project Site"},"url":"https://coastal.er.usgs.gov/fire-island/research/sandy/","text":"Fire Island Coastal Change"},{"id":298188,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0921/"},{"id":342394,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/0921/ds921_data.html","text":"April 10, 2013 Dataset"},{"id":342395,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.5066/F77H1GNN","text":"April 1, 2014 Dataset"},{"id":298193,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0921/ds921_abstract.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Report"},{"id":344812,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://coastal.er.usgs.gov/data-release/doi-F7N29VV5/","text":"January 30, 2012 Dataset"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.26370239257812,\n 40.61812224225511\n ],\n [\n -73.26370239257812,\n 40.80237530523985\n ],\n [\n -72.65121459960938,\n 40.80237530523985\n ],\n [\n -72.65121459960938,\n 40.61812224225511\n ],\n [\n -73.26370239257812,\n 40.61812224225511\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f589aee4b02419550d2f31","contributors":{"authors":[{"text":"Brenner, Owen T. 0000-0002-1588-721X obrenner@usgs.gov","orcid":"https://orcid.org/0000-0002-1588-721X","contributorId":4933,"corporation":false,"usgs":true,"family":"Brenner","given":"Owen","email":"obrenner@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":541603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":541604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spore, Nicholas J.","contributorId":139216,"corporation":false,"usgs":false,"family":"Spore","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":12700,"text":"ACE at Duck NC","active":true,"usgs":false}],"preferred":false,"id":541605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brodie, Katherine L.","contributorId":139217,"corporation":false,"usgs":false,"family":"Brodie","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":34410,"text":"USACE-Coastal Hydraulic Lab, Duck, NC","active":true,"usgs":false},{"id":12700,"text":"ACE at Duck NC","active":true,"usgs":false}],"preferred":false,"id":541607,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McNinch, Jesse E.","contributorId":93804,"corporation":false,"usgs":true,"family":"McNinch","given":"Jesse E.","affiliations":[],"preferred":false,"id":541606,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70168685,"text":"70168685 - 2015 - Comparing models of Red Knot population dynamics","interactions":[],"lastModifiedDate":"2016-02-24T14:45:15","indexId":"70168685","displayToPublicDate":"2015-03-01T15:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Comparing models of Red Knot population dynamics","docAbstract":"Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cooper Ornithological Club","publisherLocation":"Santa Clara","doi":"10.1650/CONDOR-15-9.1","usgsCitation":"McGowan, C.P., 2015, Comparing models of Red Knot population dynamics: The Condor, v. 117, no. 4, p. 494-502, https://doi.org/10.1650/CONDOR-15-9.1.","productDescription":"9 p.","startPage":"494","endPage":"502","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061278","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":472231,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-15-9.1","text":"Publisher Index Page"},{"id":318370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56cee255e4b015c306ec5e96","contributors":{"authors":[{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":621321,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70198332,"text":"70198332 - 2015 - Life in the main channel: long-term hydrologic control of microbial mat abundance in McMurdo Dry Valley streams, Antarctica","interactions":[],"lastModifiedDate":"2018-07-30T16:03:50","indexId":"70198332","displayToPublicDate":"2015-03-01T15:13:02","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Life in the main channel: long-term hydrologic control of microbial mat abundance in McMurdo Dry Valley streams, Antarctica","docAbstract":"Given alterations in global hydrologic regime, we examine the role of hydrology in regulating stream microbial mat abundance in the McMurdo Dry Valleys, Antarctica. Here, perennial mats persist as a desiccated crust until revived by summer streamflow, which varies inter-annually, and has increased since the 1990s. We predicted high flows to scour mats, and intra-seasonal drying to slow growth. Responses were hypothesized to differ based on mat location within streams, along with geomorphology, which may promote (high coverage) or discourage (low coverage) accrual. We compared hydrologic trends with the biomass of green and orange mats, which grow in the channel, and black mats growing at stream margins for 16 diverse stream transects over two decades. We found mat biomass collectively decreased during first decade coinciding with low flows, and increased following elevated discharges. Green mat biomass showed the greatest correlations with hydrology and was stimulated by discharge in high coverage transects, but negatively correlated in low coverage due to habitat scour. In contrast, orange mat biomass was negatively related to flow in high coverage transects, but positively correlated in low coverage because of side-channel expansion. Black mats were weakly correlated with all hydrologic variables regardless of coverage. Lastly, model selection indicated the best combination of predictive hydrologic variables for biomass differed between mat types, but also high and low coverage transects. These results demonstrate the importance of geomorphology and species composition to modeling primary production, and will be useful in predicting ecological responses of benthic habitats to altered hydrologic regimes.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-014-9829-6","usgsCitation":"Kohler, T.J., Stanish, L.F., Crisp, S.W., Koch, J.C., Liptzin, D., Baeseman, J.L., and McKnight, D.M., 2015, Life in the main channel: long-term hydrologic control of microbial mat abundance in McMurdo Dry Valley streams, Antarctica: Ecosystems, v. 18, no. 2, p. 310-327, https://doi.org/10.1007/s10021-014-9829-6.","productDescription":"28 p.","startPage":"310","endPage":"327","ipdsId":"IP-052879","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":356007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"McMurdo Dry Valley, Antarctica","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-12-23","publicationStatus":"PW","scienceBaseUri":"5b6fcc2de4b0f5d57878ecd1","contributors":{"authors":[{"text":"Kohler, Tyler J.","contributorId":206557,"corporation":false,"usgs":false,"family":"Kohler","given":"Tyler","email":"","middleInitial":"J.","affiliations":[{"id":25642,"text":"Institute of arctic and Alpine Research, Univ. of Co, Boulder, C","active":true,"usgs":false}],"preferred":false,"id":741108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanish, Lee F.","contributorId":206565,"corporation":false,"usgs":false,"family":"Stanish","given":"Lee","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":741109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crisp, Steven W.","contributorId":206558,"corporation":false,"usgs":false,"family":"Crisp","given":"Steven","email":"","middleInitial":"W.","affiliations":[{"id":25620,"text":"Institute of Arctic and Alpine Research, University of Colorado – Boulder","active":true,"usgs":false}],"preferred":false,"id":741110,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":741111,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liptzin, Daniel","contributorId":168551,"corporation":false,"usgs":false,"family":"Liptzin","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":741112,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baeseman, Jenny L.","contributorId":189421,"corporation":false,"usgs":false,"family":"Baeseman","given":"Jenny","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":741113,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKnight, Diane M.","contributorId":59773,"corporation":false,"usgs":false,"family":"McKnight","given":"Diane","email":"","middleInitial":"M.","affiliations":[{"id":16833,"text":"INSTAAR, University of Colorado","active":true,"usgs":false}],"preferred":false,"id":741114,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70162625,"text":"70162625 - 2015 - Risk assessment of brine contamination to aquatic resources from energy development in glacial drift deposits: Williston Basin, USA","interactions":[],"lastModifiedDate":"2016-01-27T13:38:31","indexId":"70162625","displayToPublicDate":"2015-03-01T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Risk assessment of brine contamination to aquatic resources from energy development in glacial drift deposits: Williston Basin, USA","docAbstract":"Contamination to aquatic resources from co-produced water (brine) associated with energy development has been documented in the northeastern portion of the Williston Basin; an area mantled by glacial drift. The presence and magnitude of brine contamination can be determined using the contamination index (CI) value from water samples. Recently, the U.S. Geological Survey published a section (~ 2.59 km2) level risk assessment of brine contamination to aquatic resources for Sheridan County, Montana, using oilfield and hydrogeological parameters.
\nOur goal was to improve the Sheridan County assessment (SCA) and evaluate the use of this new Williston Basin assessment (WBA) across 31 counties mantled by glacial drift in the Williston Basin. To determine if the WBA model improved the SCA model, results from both assessments were compared to CI values from 37 surface and groundwater samples collected to evaluate the SCA. The WBA (R2 = 0.65) outperformed the SCA (R2 = 0.52) indicating improved model performance. Applicability across the Williston Basin was evaluated by comparing WBA results to CI values from 123 surface water samples collected from 97 sections. Based on the WBA, the majority (83.5%) of sections lacked an oil well and had minimal risk. Sections with one or more oil wells comprised low (8.4%), moderate (6.5%), or high (1.7%) risk areas. The percentage of contaminated water samples, percentage of sections with at least one contaminated sample, and the average CI value of contaminated samples increased from low to high risk indicating applicability across the Williston Basin. Furthermore, the WBA performed better compared to only the contaminated samples (R2 = 0.62) versus all samples (R2 = 0.38). This demonstrates that the WBA was successful at identifying sections, but not individual aquatic resources, with an increased risk of contamination; therefore, WBA results can prioritize future sampling within areas of increased risk.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science of the Total Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.scitotenv.2014.11.054","collaboration":"USFWS Region 6 Inventory and Monitoring Program","usgsCitation":"Preston, T.M., and Chesley-Preston, T.L., 2015, Risk assessment of brine contamination to aquatic resources from energy development in glacial drift deposits: Williston Basin, USA: Science of the Total Environment, v. 508, p. 534-545, https://doi.org/10.1016/j.scitotenv.2014.11.054.","productDescription":"12 p.","startPage":"534","endPage":"545","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059481","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":314928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.16259765625,\n 48.96579381461063\n ],\n [\n -109.40185546874999,\n 48.99463598353405\n ],\n [\n -109.57763671875,\n 47.82790816919327\n ],\n [\n -108.43505859374999,\n 47.635783590864854\n ],\n [\n -107.77587890625,\n 47.54687159892238\n ],\n [\n -106.8310546875,\n 47.7097615426664\n ],\n [\n -106.50146484374999,\n 48.019324184801185\n ],\n [\n -104.9853515625,\n 48.09275716032736\n ],\n [\n -104.765625,\n 48.04870994288686\n ],\n [\n -103.9306640625,\n 47.97521412341618\n ],\n [\n -103.71093749999999,\n 48.122101028190805\n ],\n [\n -103.447265625,\n 47.945786463687185\n ],\n [\n -103.1396484375,\n 48.1367666796927\n ],\n [\n -102.568359375,\n 48.03401915864286\n ],\n [\n -102.26074218749999,\n 47.66538735632654\n ],\n [\n -101.8212890625,\n 47.487513008956554\n ],\n [\n -101.337890625,\n 47.56170075451973\n ],\n [\n -101.337890625,\n 47.249406957888446\n ],\n [\n -100.986328125,\n 47.249406957888446\n ],\n [\n -100.8984375,\n 46.89023157359399\n ],\n [\n -100.5908203125,\n 46.51351558059737\n ],\n [\n -100.5029296875,\n 46.28622391806708\n ],\n [\n -100.6787109375,\n 46.10370875598026\n ],\n [\n -100.45898437499999,\n 45.96642454131025\n ],\n [\n -99.5361328125,\n 45.9511496866914\n ],\n [\n -98.228759765625,\n 45.96642454131025\n ],\n [\n -98.162841796875,\n 46.927758623434435\n ],\n [\n -97.987060546875,\n 47.71715357016648\n ],\n [\n -98.15185546874999,\n 48.29781249243716\n ],\n [\n -98.81103515625,\n 49.001843917978526\n ],\n [\n -99.16259765625,\n 48.96579381461063\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"508","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56a9f84be4b012c193aa3edc","contributors":{"authors":[{"text":"Preston, Todd M. 0000-0002-8812-9233 tmpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":1664,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"tmpreston@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":589941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chesley-Preston, Tara L. tchesley-preston@usgs.gov","contributorId":5557,"corporation":false,"usgs":true,"family":"Chesley-Preston","given":"Tara","email":"tchesley-preston@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":589942,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70143179,"text":"70143179 - 2015 - Distance measures and optimization spaces in quantitative fatty acid signature analysis","interactions":[],"lastModifiedDate":"2018-04-23T10:22:40","indexId":"70143179","displayToPublicDate":"2015-03-01T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Distance measures and optimization spaces in quantitative fatty acid signature analysis","docAbstract":"Quantitative fatty acid signature analysis has become an important method of diet estimation in ecology, especially marine ecology. Controlled feeding trials to validate the method and estimate the calibration coefficients necessary to account for differential metabolism of individual fatty acids have been conducted with several species from diverse taxa. However, research into potential refinements of the estimation method has been limited. We compared the performance of the original method of estimating diet composition with that of five variants based on different combinations of distance measures and calibration-coefficient transformations between prey and predator fatty acid signature spaces. Fatty acid signatures of pseudopredators were constructed using known diet mixtures of two prey data sets previously used to estimate the diets of polar bears Ursus maritimus and gray seals Halichoerus grypus, and their diets were then estimated using all six variants. In addition, previously published diets of Chukchi Sea polar bears were re-estimated using all six methods. Our findings reveal that the selection of an estimation method can meaningfully influence estimates of diet composition. Among the pseudopredator results, which allowed evaluation of bias and precision, differences in estimator performance were rarely large, and no one estimator was universally preferred, although estimators based on the Aitchison distance measure tended to have modestly superior properties compared to estimators based on the Kullback-Leibler distance measure. However, greater differences were observed among estimated polar bear diets, most likely due to differential estimator sensitivity to assumption violations. Our results, particularly the polar bear example, suggest that additional research into estimator performance and model diagnostics is warranted.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1429","usgsCitation":"Bromaghin, J.F., Rode, K.D., Budge, S.M., and Thiemann, G.W., 2015, Distance measures and optimization spaces in quantitative fatty acid signature analysis: Ecology and Evolution, v. 6, no. 5, p. 1249-1262, https://doi.org/10.1002/ece3.1429.","productDescription":"14 p.","startPage":"1249","endPage":"1262","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059904","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":472234,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1429","text":"Publisher Index Page"},{"id":298624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-24","publicationStatus":"PW","scienceBaseUri":"5509502ee4b02e76d757e614","contributors":{"authors":[{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":542494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":542495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budge, Suzanne M.","contributorId":92168,"corporation":false,"usgs":false,"family":"Budge","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":542496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiemann, Gregory W.","contributorId":83023,"corporation":false,"usgs":false,"family":"Thiemann","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":542497,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70157354,"text":"70157354 - 2015 - Strain accumulation across the Prince William Sound asperity, Southcentral Alaska","interactions":[],"lastModifiedDate":"2015-09-23T11:27:52","indexId":"70157354","displayToPublicDate":"2015-03-01T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Strain accumulation across the Prince William Sound asperity, Southcentral Alaska","docAbstract":"The surface velocities predicted by the conventional subduction model are compared to velocities measured in a GPS array (surveyed in 1993, 1995, 1997, 2000, and 2004) spanning the Prince William Sound asperity. The observed velocities in the comparison have been corrected to remove the contributions from postseismic (1964 Alaska earthquake) mantle relaxation. Except at the most seaward monument (located on Middleton Island at the seaward edge of the continental shelf, just 50 km landward of the deformation front in the Aleutian Trench), the corrected velocities qualitatively agree with those predicted by an improved, two-dimensional, back slip, subduction model in which the locked megathrust coincides with the plate interface identified by seismic refraction surveys, and the back slip rate is equal to the plate convergence rate. A better fit to the corrected velocities is furnished by either a back slip rate 20% greater than the plate convergence rate or a 30% shallower megathrust. The shallow megathrust in the latter fit may be an artifact of the uniform half-space Earth model used in the inversion. Backslip at the plate convergence rate on the megathrust mapped by refraction surveys would fit the data as well if the rigidity of the underthrust plate was twice that of the overlying plate, a rigidity contrast higher than expected. The anomalous motion at Middleton Island is attributed to continuous slip at near the plate convergence rate on a postulated, listric fault that splays off the megathrust at depth of about 12 km and outcrops on the continental slope south-southeast of Middleton Island.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2014JB011652","usgsCitation":"Savage, J.C., Svarc, J.L., and Lisowski, M., 2015, Strain accumulation across the Prince William Sound asperity, Southcentral Alaska: Journal of Geophysical Research B: Solid Earth, v. 120, no. 3, p. 1820-1832, https://doi.org/10.1002/2014JB011652.","productDescription":"13 p.","startPage":"1820","endPage":"1832","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055343","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472235,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014jb011652","text":"Publisher Index Page"},{"id":308440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-09","publicationStatus":"PW","scienceBaseUri":"5603cd5be4b03bc34f544b40","contributors":{"authors":[{"text":"Savage, James C. 0000-0002-5114-7673 jasavage@usgs.gov","orcid":"https://orcid.org/0000-0002-5114-7673","contributorId":2412,"corporation":false,"usgs":true,"family":"Savage","given":"James","email":"jasavage@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":572822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Svarc, Jerry L. 0000-0002-2802-4528 jsvarc@usgs.gov","orcid":"https://orcid.org/0000-0002-2802-4528","contributorId":2413,"corporation":false,"usgs":true,"family":"Svarc","given":"Jerry","email":"jsvarc@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":572823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lisowski, Michael 0000-0003-4818-2504 mlisowski@usgs.gov","orcid":"https://orcid.org/0000-0003-4818-2504","contributorId":637,"corporation":false,"usgs":true,"family":"Lisowski","given":"Michael","email":"mlisowski@usgs.gov","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":572824,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70155022,"text":"70155022 - 2015 - The data quality analyzer: a quality control program for seismic data","interactions":[],"lastModifiedDate":"2018-02-07T19:04:03","indexId":"70155022","displayToPublicDate":"2015-03-01T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"The data quality analyzer: a quality control program for seismic data","docAbstract":"The U.S. Geological Survey's Albuquerque Seismological Laboratory (ASL) has several initiatives underway to enhance and track the quality of data produced from ASL seismic stations and to improve communication about data problems to the user community. The Data Quality Analyzer (DQA) is one such development and is designed to characterize seismic station data quality in a quantitative and automated manner.
\nThe DQA consists of a metric calculator, a PostgreSQL database, and a Web interface: The metric calculator, SEEDscan, is a Java application that reads and processes miniSEED data and generates metrics based on a configuration file. SEEDscan compares hashes of metadata and data to detect changes in either and performs subsequent recalculations as needed. This ensures that the metric values are up to date and accurate. SEEDscan can be run as a scheduled task or on demand. The PostgreSQL database acts as a central hub where metric values and limited station descriptions are stored at the channel level with one-day granularity. The Web interface dynamically loads station data from the database and allows the user to make requests for time periods of interest, review specific networks and stations, plot metrics as a function of time, and adjust the contribution of various metrics to the overall quality grade of the station.
\nThe quantification of data quality is based on the evaluation of various metrics (e.g., timing quality, daily noise levels relative to long-term noise models, and comparisons between broadband data and event synthetics). Users may select which metrics contribute to the assessment and those metrics are aggregated into a “grade” for each station. The DQA is being actively used for station diagnostics and evaluation based on the completed metrics (availability, gap count, timing quality, deviation from a global noise model, deviation from a station noise model, coherence between co-located sensors, and comparison between broadband data and synthetics for earthquakes) on stations in the Global Seismographic Network and Advanced National Seismic System.
","language":"English","publisher":"Computer Oriented Geological Society","publisherLocation":"Oxford","doi":"10.1016/j.cageo.2014.12.006","usgsCitation":"Ringler, A.T., Hagerty, M., Holland, J., Gonzales, A., Gee, L.S., Edwards, J., Wilson, D.C., and Baker, A., 2015, The data quality analyzer: a quality control program for seismic data: Computers & Geosciences, v. 76, p. 96-111, https://doi.org/10.1016/j.cageo.2014.12.006.","productDescription":"16 p.","startPage":"96","endPage":"111","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061275","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":305952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b361b6e4b09a3b01b5dabb","contributors":{"authors":[{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hagerty, M.T.","contributorId":145577,"corporation":false,"usgs":false,"family":"Hagerty","given":"M.T.","email":"","affiliations":[{"id":13422,"text":"Boston College","active":true,"usgs":false}],"preferred":false,"id":564684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holland, James F. jholland@usgs.gov","contributorId":5334,"corporation":false,"usgs":true,"family":"Holland","given":"James F.","email":"jholland@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonzales, A.","contributorId":145578,"corporation":false,"usgs":false,"family":"Gonzales","given":"A.","email":"","affiliations":[{"id":16157,"text":"Honeywell Technology Solutions Incoporation","active":true,"usgs":false}],"preferred":false,"id":564686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gee, Lind S. lgee@usgs.gov","contributorId":145579,"corporation":false,"usgs":true,"family":"Gee","given":"Lind","email":"lgee@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":564687,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Edwards, J.D.","contributorId":69622,"corporation":false,"usgs":true,"family":"Edwards","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":564688,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564689,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baker, Adam ambaker@usgs.gov","contributorId":145581,"corporation":false,"usgs":true,"family":"Baker","given":"Adam","email":"ambaker@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":564690,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70155019,"text":"70155019 - 2015 - Evolution of pathogen virulence across space during an epidemic","interactions":[],"lastModifiedDate":"2015-07-24T10:59:00","indexId":"70155019","displayToPublicDate":"2015-03-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":740,"text":"American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Evolution of pathogen virulence across space during an epidemic","docAbstract":"We explore pathogen virulence evolution during the spatial expansion of an infectious disease epidemic in the presence of a novel host movement trade-off, using a simple, spatially explicit mathematical model. This work is motivated by empirical observations of the Mycoplasma gallisepticum invasion into North American house finch (Haemorhous mexicanus) populations; however, our results likely have important applications to other emerging infectious diseases in mobile hosts. We assume that infection reduces host movement and survival and that across pathogen strains the severity of these reductions increases with pathogen infectiousness. Assuming these trade-offs between pathogen virulence (host mortality), pathogen transmission, and host movement, we find that pathogen virulence levels near the epidemic front (that maximize wave speed) are lower than those that have a short-term growth rate advantage or that ultimately prevail (i.e., are evolutionarily stable) near the epicenter and where infection becomes endemic (i.e., that maximize the pathogen basic reproductive ratio). We predict that, under these trade-offs, less virulent pathogen strains will dominate the periphery of an epidemic and that more virulent strains will increase in frequency after invasion where disease is endemic. These results have important implications for observing and interpreting spatiotemporal epidemic data and may help explain transient virulence dynamics of emerging infectious diseases.
","language":"English","publisher":"American Society of Naturalists","publisherLocation":"Salem, MA","doi":"10.1086/679734","usgsCitation":"Osnas, E.E., Hurtado, P.J., and Dobson, A.P., 2015, Evolution of pathogen virulence across space during an epidemic: American Naturalist, v. 185, no. 3, p. 332-342, https://doi.org/10.1086/679734.","productDescription":"11 p.","startPage":"332","endPage":"342","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059359","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472236,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/679734","text":"Publisher Index Page"},{"id":305950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b361b0e4b09a3b01b5da9c","contributors":{"authors":[{"text":"Osnas, Erik E. 0000-0001-9528-0866 eosnas@usgs.gov","orcid":"https://orcid.org/0000-0001-9528-0866","contributorId":5586,"corporation":false,"usgs":true,"family":"Osnas","given":"Erik","email":"eosnas@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":564672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurtado, Paul J.","contributorId":145574,"corporation":false,"usgs":false,"family":"Hurtado","given":"Paul","email":"","middleInitial":"J.","affiliations":[{"id":6714,"text":"Ohio State University, School of Earth Sciences, Columbus, Ohio, USA","active":true,"usgs":false}],"preferred":false,"id":564673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dobson, Andrew P.","contributorId":63693,"corporation":false,"usgs":true,"family":"Dobson","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":564674,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048750,"text":"70048750 - 2015 - Hawaiian fissure fountains: Quantifying vent and shallow conduit geometry, episode 1 of the 1969-1974 Mauna Ulu eruption","interactions":[],"lastModifiedDate":"2022-12-29T15:39:25.607531","indexId":"70048750","displayToPublicDate":"2015-03-01T11:43:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"17","title":"Hawaiian fissure fountains: Quantifying vent and shallow conduit geometry, episode 1 of the 1969-1974 Mauna Ulu eruption","docAbstract":"Geometries of shallow magmatic pathways feeding volcanic eruptions are poorly constrained, yet many key interpretations about eruption dynamics depend on knowledge of these geometries. Direct quantification is difficult because vents typically become blocked with lava at the end of eruptions. Indirect geophysical techniques have shed light on some volcanic conduit geometries, but the scales are too coarse to resolve narrow fissures (widths typically 1 m). Kīlauea's Mauna Ulu eruption, which started with <50 m high Hawaiian fountains along a 4.5 km fissure on 24 May 1969, provides a unique opportunity to measure the detailed geometry of a shallow magmatic pathway, as the western vents remain unobstructed to depths >30 m. Direct measurements at the ground surface were augmented by tripod-mounted lidar measurements to quantify the shallow conduit geometry for three vents at a resolution <4 cm. We define the form of the fissure in terms of aspect ratio, flaring ratio, irregularity, sinuosity, and segmentation and discuss the factors influencing these parameters. In the past, simplified first-order fissure geometries have been used in computational modeling. Our data can provide more accurate conduit shapes for better understanding of shallow fissure fluid dynamics and how it controls eruptive behavior, especially if incorporated into computer models.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Hawaiian volcanoes: From source to surface","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"AGU Chapman Conference","conferenceDate":"August 20-24, 2012","conferenceLocation":"Waikoloa, Hawai'i","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/9781118872079.ch17","usgsCitation":"Parcheta, C., Fagents, S., Swanson, D., Houghton, B.F., and Ericksen, T., 2015, Hawaiian fissure fountains: Quantifying vent and shallow conduit geometry, episode 1 of the 1969-1974 Mauna Ulu eruption, chap. 17 of Hawaiian volcanoes: From source to surface, v. 208, p. 369-391, https://doi.org/10.1002/9781118872079.ch17.","productDescription":"23 p.","startPage":"369","endPage":"391","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050831","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":311101,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Ulu Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.21106719970703,\n 19.37253100428563\n ],\n [\n -155.1870346069336,\n 19.3741504184188\n ],\n [\n -155.18394470214844,\n 19.35520226587889\n ],\n [\n -155.20832061767578,\n 19.355364225230744\n ],\n [\n -155.21106719970703,\n 19.37253100428563\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"208","noUsgsAuthors":false,"publicationDate":"2015-02-27","publicationStatus":"PW","scienceBaseUri":"563ddd41e4b0831b7d6271ed","contributors":{"editors":[{"text":"Carey, Rebecca","contributorId":121557,"corporation":false,"usgs":true,"family":"Carey","given":"Rebecca","affiliations":[],"preferred":false,"id":692144,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cayol, Valerie","contributorId":121509,"corporation":false,"usgs":false,"family":"Cayol","given":"Valerie","email":"","affiliations":[],"preferred":false,"id":692145,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":127857,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":692146,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Weis, Dominique","contributorId":121531,"corporation":false,"usgs":true,"family":"Weis","given":"Dominique","affiliations":[],"preferred":false,"id":692147,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Parcheta, Carolyn","contributorId":115234,"corporation":false,"usgs":true,"family":"Parcheta","given":"Carolyn","affiliations":[],"preferred":false,"id":518229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fagents, Sarah","contributorId":116991,"corporation":false,"usgs":true,"family":"Fagents","given":"Sarah","affiliations":[],"preferred":false,"id":518230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swanson, Donald A. 0000-0002-1680-3591 donswan@usgs.gov","orcid":"https://orcid.org/0000-0002-1680-3591","contributorId":3137,"corporation":false,"usgs":true,"family":"Swanson","given":"Donald A.","email":"donswan@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":518226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false},{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":518228,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ericksen, Todd","contributorId":25484,"corporation":false,"usgs":true,"family":"Ericksen","given":"Todd","affiliations":[],"preferred":false,"id":518227,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70147491,"text":"70147491 - 2015 - Quaternary tephrochronology and deposition in the subsurface Sacramento–San Joaquin Delta, California, U.S.A.","interactions":[],"lastModifiedDate":"2021-08-31T16:01:18.181621","indexId":"70147491","displayToPublicDate":"2015-03-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Quaternary tephrochronology and deposition in the subsurface Sacramento–San Joaquin Delta, California, U.S.A.","docAbstract":"We document characteristics of tephra, including facies and geochemistry, from 27 subsurface sites in the Sacramento-San Joaquin Delta, California, to obtain stratigraphic constraints in a complex setting. Analyzed discrete tephra deposits are correlative with: 1) an unnamed tephra from the Carlotta Formation near Ferndale, California, herein informally named the ash of Wildcat Grade (<~1.450 - >~0.780 Ma), 2) the Rockland ash bed (~0.575 Ma), 3) the Loleta ash bed (~0.390 Ma), and 4) a middle Pleistocene tephra resembling volcanic ash deposits at Tulelake, California, and Pringle Falls, Bend, and Summer Lake, Oregon, herein informally named the dacitic ash of Hood (<~0.211 to >~0.180 Ma, correlated age). All four tephra are derived from Cascades volcanic sources. The Rockland ash bed erupted from the southern Cascades near Lassen Peak, California, and occurs in deposits up to >7 m thick as observed in core samples taken from ~40 m depth below land surface. Tephra facies and tephra age constraints suggest rapid tephra deposition within fluvial channel and overbank settings, likely related to flood events shortly following the volcanic eruption. Such rapidly deposited tephra are important chronostratigraphic markers that suggest varying sediment accumulation rates (~0.07-0.29 m/1000 yr) in Quaternary deposits below the modern Sacramento-San Joaquin Delta. This study provides the first steps in developing a subsurface Quaternary stratigraphic framework necessary for future hazard assessment.
","language":"English","publisher":"American Quaternary Association","publisherLocation":"New York, NY","doi":"10.1016/j.yqres.2014.12.007","usgsCitation":"Maier, K., Gatti, E., Wan, E., Ponti, D.J., Pagenkopp, M., Starratt, S.W., Olson, H.A., and Tinsley, J., 2015, Quaternary tephrochronology and deposition in the subsurface Sacramento–San Joaquin Delta, California, U.S.A.: Quaternary Research, v. 83, no. 2, p. 378-393, https://doi.org/10.1016/j.yqres.2014.12.007.","productDescription":"16 p.","startPage":"378","endPage":"393","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052550","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":300032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.8771743774414,\n 38.012664749652494\n ],\n [\n -121.8771743774414,\n 38.078365629967145\n ],\n [\n -121.78070068359375,\n 38.078365629967145\n ],\n [\n -121.78070068359375,\n 38.012664749652494\n ],\n [\n -121.8771743774414,\n 38.012664749652494\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-20","publicationStatus":"PW","scienceBaseUri":"55489850e4b0a658d7960d7c","chorus":{"doi":"10.1016/j.yqres.2014.12.007","url":"http://dx.doi.org/10.1016/j.yqres.2014.12.007","publisher":"Cambridge University Press (CUP)","authors":"Maier Katherine L., Gatti Emma, Wan Elmira, Ponti Daniel J., Pagenkopp Mark, Starratt Scott W., Olson Holly A., Tinsley John C.","journalName":"Quaternary Research","publicationDate":"3/2015","auditedOn":"3/9/2015"},"contributors":{"authors":[{"text":"Maier, Katherine L.","contributorId":91411,"corporation":false,"usgs":true,"family":"Maier","given":"Katherine L.","affiliations":[],"preferred":false,"id":546047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gatti, Emma egatti@usgs.gov","contributorId":5302,"corporation":false,"usgs":true,"family":"Gatti","given":"Emma","email":"egatti@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":546031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wan, Elmira 0000-0002-9255-112X ewan@usgs.gov","orcid":"https://orcid.org/0000-0002-9255-112X","contributorId":3434,"corporation":false,"usgs":true,"family":"Wan","given":"Elmira","email":"ewan@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":546032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ponti, Daniel J. 0000-0002-2437-5144 dponti@usgs.gov","orcid":"https://orcid.org/0000-0002-2437-5144","contributorId":1020,"corporation":false,"usgs":true,"family":"Ponti","given":"Daniel","email":"dponti@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":546033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pagenkopp, Mark","contributorId":102802,"corporation":false,"usgs":true,"family":"Pagenkopp","given":"Mark","email":"","affiliations":[],"preferred":false,"id":546034,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":546035,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olson, Holly A. holson@usgs.gov","contributorId":5305,"corporation":false,"usgs":true,"family":"Olson","given":"Holly","email":"holson@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":546036,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tinsley, John jtinsley@usgs.gov","contributorId":140545,"corporation":false,"usgs":true,"family":"Tinsley","given":"John","email":"jtinsley@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":546037,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70147094,"text":"70147094 - 2015 - Long‐term time‐dependent probabilities for the third Uniform California Earthquake Rupture Forecast (UCERF3)","interactions":[],"lastModifiedDate":"2015-04-28T09:15:02","indexId":"70147094","displayToPublicDate":"2015-03-01T10:15:00","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":"Long‐term time‐dependent probabilities for the third Uniform California Earthquake Rupture Forecast (UCERF3)","docAbstract":"The 2014 Working Group on California Earthquake Probabilities (WGCEP 2014) presents time-dependent earthquake probabilities for the third Uniform California Earthquake Rupture Forecast (UCERF3). Building on the UCERF3 time-independent model, published previously, renewal models are utilized to represent elastic-rebound-implied probabilities. A new methodology has been developed that solves applicability issues in the previous approach for un-segmented models. The new methodology also supports magnitude-dependent aperiodicity and accounts for the historic open interval on faults that lack a date-of-last-event constraint. Epistemic uncertainties are represented with a logic tree, producing 5,760 different forecasts. Results for a variety of evaluation metrics are presented, including logic-tree sensitivity analyses and comparisons to the previous model (UCERF2). For 30-year M≥6.7 probabilities, the most significant changes from UCERF2 are a threefold increase on the Calaveras fault and a threefold decrease on the San Jacinto fault. Such changes are due mostly to differences in the time-independent models (e.g., fault slip rates), with relaxation of segmentation and inclusion of multi-fault ruptures being particularly influential. In fact, some UCERF2 faults were simply too long to produce M 6.7 sized events given the segmentation assumptions in that study. Probability model differences are also influential, with the implied gains (relative to a Poisson model) being generally higher in UCERF3. Accounting for the historic open interval is one reason. Another is an effective 27% increase in the total elastic-rebound-model weight. The exact factors influencing differences between UCERF2 and UCERF3, as well as the relative importance of logic-tree branches, vary throughout the region, and depend on the evaluation metric of interest. For example, M≥6.7 probabilities may not be a good proxy for other hazard or loss measures. This sensitivity, coupled with the approximate nature of the model and known limitations, means the applicability of UCERF3 should be evaluated on a case-by-case basis.
","language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford, CA","doi":"10.1785/0120140093","usgsCitation":"Field, E., Biasi, G.P., Bird, P., Dawson, T.E., Felzer, K.R., Jackson, D.A., Johnson, K.M., Jordan, T.H., Madden, C., Michael, A.J., Milner, K., Page, M.T., Parsons, T.E., Powers, P., Shaw, B., Thatcher, W.R., Weldon, R.J., and Zeng, Y., 2015, Long‐term time‐dependent probabilities for the third Uniform California Earthquake Rupture Forecast (UCERF3): Bulletin of the Seismological Society of America, v. 105, no. 2A, p. 511-543, https://doi.org/10.1785/0120140093.","productDescription":"33 p.","startPage":"511","endPage":"543","numberOfPages":"33","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061354","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":299910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"2A","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-10","publicationStatus":"PW","scienceBaseUri":"5540af2ce4b0a658d79392ad","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":545633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biasi, Glenn P.","contributorId":20436,"corporation":false,"usgs":true,"family":"Biasi","given":"Glenn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":545634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bird, Peter","contributorId":78643,"corporation":false,"usgs":true,"family":"Bird","given":"Peter","affiliations":[],"preferred":false,"id":545635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dawson, Timothy E.","contributorId":24429,"corporation":false,"usgs":false,"family":"Dawson","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":7099,"text":"Calif. 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II","contributorId":47859,"corporation":false,"usgs":true,"family":"Weldon","given":"Ray","suffix":"II","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":545679,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zeng, Yuehua zeng@usgs.gov","contributorId":1623,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":545680,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70148074,"text":"70148074 - 2015 - Small mammal use of native warm-season and non-native cool-season grass forage fields","interactions":[],"lastModifiedDate":"2015-05-19T08:55:50","indexId":"70148074","displayToPublicDate":"2015-03-01T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Small mammal use of native warm-season and non-native cool-season grass forage fields","docAbstract":"Recent emphasis has been put on establishing native warm-season grasses for forage production because it is thought native warm-season grasses provide higher quality wildlife habitat than do non-native cool-season grasses. However, it is not clear whether native warm-season grass fields provide better resources for small mammals than currently are available in non-native cool-season grass forage production fields. We developed a hierarchical spatially explicit capture-recapture model to compare abundance of hispid cotton rats (Sigmodon hispidus), white-footed mice (Peromyscus leucopus), and house mice (Mus musculus) among 4 hayed non-native cool-season grass fields, 4 hayed native warm-season grass fields, and 4 native warm-season grass-forb (\"wildlife\") fields managed for wildlife during 2 summer trapping periods in 2009 and 2010 of the western piedmont of North Carolina, USA. Cotton rat abundance estimates were greater in wildlife fields than in native warm-season grass and non-native cool-season grass fields and greater in native warm-season grass fields than in non-native cool-season grass fields. Abundances of white-footed mouse and house mouse populations were lower in wildlife fields than in native warm-season grass and non-native cool-season grass fields, but the abundances were not different between the native warm-season grass and non-native cool-season grass fields. Lack of cover following haying in non-native cool-season grass and native warm-season grass fields likely was the key factor limiting small mammal abundance, especially cotton rats, in forage fields. Retention of vegetation structure in managed forage production systems, either by alternately resting cool-season and warm-season grass forage fields or by leaving unharvested field borders, should provide refugia for small mammals during haying events.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Washington, D.C.","doi":"10.1002/wsb.507","usgsCitation":"Klimstra, R.L., Moorman, C.E., Converse, S.J., Royle, J.A., and Harper, C.A., 2015, Small mammal use of native warm-season and non-native cool-season grass forage fields: Wildlife Society Bulletin, v. 39, no. 1, p. 49-55, https://doi.org/10.1002/wsb.507.","productDescription":"7 p.","startPage":"49","endPage":"55","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056857","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":499977,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/3aba7bcedd5e4df68ec830015a2dc12a","text":"External Repository"},{"id":300527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-04","publicationStatus":"PW","scienceBaseUri":"555c5eb9e4b0a92fa7eacc0e","contributors":{"authors":[{"text":"Klimstra, Ryan L","contributorId":140840,"corporation":false,"usgs":false,"family":"Klimstra","given":"Ryan","email":"","middleInitial":"L","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":547170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moorman, Christopher E.","contributorId":140839,"corporation":false,"usgs":false,"family":"Moorman","given":"Christopher","email":"","middleInitial":"E.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":547169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":3513,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":547168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":547171,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harper, Craig A","contributorId":140841,"corporation":false,"usgs":false,"family":"Harper","given":"Craig","email":"","middleInitial":"A","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":547172,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70174829,"text":"70174829 - 2015 - Quantifying suspended sediment loads delivered to Cheney Reservoir, Kansas: Temporal patterns and management implications","interactions":[],"lastModifiedDate":"2016-07-18T11:37:50","indexId":"70174829","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying suspended sediment loads delivered to Cheney Reservoir, Kansas: Temporal patterns and management implications","docAbstract":"Cheney Reservoir, constructed during 1962 to 1965, is the primary water supply for the city of Wichita, the largest city in Kansas. Sediment is an important concern for the reservoir as it degrades water quality and progressively decreases water storage capacity. Long-term data collection provided a unique opportunity to estimate the annual suspended sediment loads for the entire history of the reservoir. To quantify and characterize sediment loading to Cheney Reservoir, discrete suspended sediment samples and continuously measured streamflow data were collected from the North Fork Ninnescah River, the primary inflow to Cheney Reservoir, over a 48-year period. Continuous turbidity data also were collected over a 15-year period. These data were used together to develop simple linear regression models to compute continuous suspended sediment concentrations and loads from 1966 to 2013. The inclusion of turbidity as an additional explanatory variable with streamflow improved regression model diagnostics and increased the amount of variability in suspended sediment concentration explained by 14%. Using suspended sediment concentration from the streamflow-only model, the average annual suspended sediment load was 102,517 t (113,006 tn) and ranged from 4,826 t (5,320 tn) in 1966 to 967,569 t (1,066,562 tn) in 1979. The sediment load in 1979 accounted for about 20% of the total load over the 48-year history of the reservoir and 92% of the 1979 sediment load occurred in one 24-hour period during a 1% annual exceedance probability flow event (104-year flood). Nearly 60% of the reservoir sediment load during the 48-year study period occurred in 5 years with extreme flow events (9% to 1% annual exceedance probability, or 11- to 104-year flood events). A substantial portion (41%) of sediment was transported to the reservoir during five storm events spanning only eight 24-hour periods during 1966 to 2013. Annual suspended sediment load estimates based on streamflow were, on average, within ±20% of estimates based on streamflow and turbidity combined. Results demonstrate that large suspended sediment loads are delivered to Cheney Reservoir in very short time periods, indicating that sediment management plans eventually must address large, infrequent inflow events to be effective.
","language":"English","publisher":"Soil and Water Conservation Society","doi":"10.2489/jswc.70.2.91","usgsCitation":"Stone, M.L., Juracek, K.E., Graham, J., and Foster, G.M., 2015, Quantifying suspended sediment loads delivered to Cheney Reservoir, Kansas: Temporal patterns and management implications: Journal of Soil and Water Conservation, v. 70, no. 2, p. 91-100, https://doi.org/10.2489/jswc.70.2.91.","productDescription":"10 p.","startPage":"91","endPage":"100","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058102","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":472250,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2489/jswc.70.2.91","text":"Publisher Index Page"},{"id":325358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Cheney Reservoir Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.0692138671875,\n 37.67077737288316\n ],\n [\n -99.0692138671875,\n 38.01564013749379\n ],\n [\n -97.77145385742188,\n 38.01564013749379\n ],\n [\n -97.77145385742188,\n 37.67077737288316\n ],\n [\n -99.0692138671875,\n 37.67077737288316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"70","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-12","publicationStatus":"PW","scienceBaseUri":"578dfdb8e4b0f1bea0e0f8e1","contributors":{"authors":[{"text":"Stone, Mandy L. 0000-0002-6711-1536 mstone@usgs.gov","orcid":"https://orcid.org/0000-0002-6711-1536","contributorId":4409,"corporation":false,"usgs":true,"family":"Stone","given":"Mandy","email":"mstone@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":642667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Juracek, Kyle E. 0000-0002-2102-8980 kjuracek@usgs.gov","orcid":"https://orcid.org/0000-0002-2102-8980","contributorId":2022,"corporation":false,"usgs":true,"family":"Juracek","given":"Kyle","email":"kjuracek@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":642668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":642669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, Guy M. 0000-0002-9581-057X gfoster@usgs.gov","orcid":"https://orcid.org/0000-0002-9581-057X","contributorId":149145,"corporation":false,"usgs":true,"family":"Foster","given":"Guy","email":"gfoster@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642670,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70171532,"text":"70171532 - 2015 - Uranium isotopes and dissolved organic carbon in loess permafrost: Modeling the age of ancient ice","interactions":[],"lastModifiedDate":"2016-06-02T09:30:58","indexId":"70171532","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Uranium isotopes and dissolved organic carbon in loess permafrost: Modeling the age of ancient ice","docAbstract":"The residence time of ice in permafrost is an indicator of past climate history, and of the resilience and vulnerability of high-latitude ecosystems to global change. Development of geochemical indicators of ground-ice residence times in permafrost will advance understanding of the circumstances and evidence of permafrost formation, preservation, and thaw in response to climate warming and other disturbance. We used uranium isotopes to evaluate the residence time of segregated ground ice from ice-rich loess permafrost cores in central Alaska. Activity ratios of 234U vs. 238U (234U/238U) in water from thawed core sections ranged between 1.163 and 1.904 due to contact of ice and associated liquid water with mineral surfaces over time. Measured (234U/238U) values in ground ice showed an overall increase with depth in a series of five neighboring cores up to 21 m deep. This is consistent with increasing residence time of ice with depth as a result of accumulation of loess over time, as well as characteristic ice morphologies, high segregated ice content, and wedge ice, all of which support an interpretation of syngenetic permafrost formation associated with loess deposition. At the same time, stratigraphic evidence indicates some past sediment redistribution and possibly shallow thaw among cores, with local mixing of aged thaw waters. Using measures of surface area and a leaching experiment to determine U distribution, a geometric model of (234U/238U) evolution suggests mean ages of up to ∼200 ky BP in the deepest core, with estimated uncertainties of up to an order of magnitude. Evidence of secondary coatings on loess grains with elevated (234U/238U) values and U concentrations suggests that refinement of the geometric model to account for weathering processes is needed to reduce uncertainty. We suggest that in this area of deep ice-rich loess permafrost, ice bodies have been preserved from the last glacial period (10–100 ky BP), despite subsequent fluctuations in climate, fire disturbance and vegetation. Radiocarbon (14C) analysis of dissolved organic carbon (DOC) in thaw waters supports ages greater than ∼40 ky BP below 10 m. DOC concentrations in thaw waters increased with depth to maxima of >1000 ppm, despite little change in ice content or cryostructures. These relations suggest time-dependent production of old DOC that will be released upon permafrost thaw at a rate that is mediated by sediment transport, among other factors.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2014.11.008","usgsCitation":"Ewing, S.A., Paces, J.B., O'Donnell, J., Jorgenson, M., Kanevskiy, M., Aiken, G.R., Shur, Y., Harden, J.W., and Striegl, R.G., 2015, Uranium isotopes and dissolved organic carbon in loess permafrost: Modeling the age of ancient ice: Geochimica et Cosmochimica Acta, v. 152, p. 143-165, https://doi.org/10.1016/j.gca.2014.11.008.","productDescription":"23 p.","startPage":"143","endPage":"165","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052832","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":472249,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.montana.edu/xmlui/handle/1/9102","text":"External Repository"},{"id":322077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Hess Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.721435546875,\n 65.09989850223572\n ],\n [\n -150.721435546875,\n 66.09381676305271\n ],\n [\n -146.546630859375,\n 66.09381676305271\n ],\n [\n -146.546630859375,\n 65.09989850223572\n ],\n [\n -150.721435546875,\n 65.09989850223572\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"152","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575158bde4b053f0edd03ca0","chorus":{"doi":"10.1016/j.gca.2014.11.008","url":"http://dx.doi.org/10.1016/j.gca.2014.11.008","publisher":"Elsevier BV","authors":"Ewing S.A., Paces J.B., O’Donnell J.A., Jorgenson M.T., Kanevskiy M.Z., Aiken G.R., Shur Y., Harden J.W., Striegl R.","journalName":"Geochimica et Cosmochimica Acta","publicationDate":"3/2015","auditedOn":"2/28/2015"},"contributors":{"authors":[{"text":"Ewing, Stephanie A.","contributorId":50065,"corporation":false,"usgs":true,"family":"Ewing","given":"Stephanie","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":631626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paces, James B. 0000-0002-9809-8493 jbpaces@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":2514,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"jbpaces@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":631627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Donnell, J.A.","contributorId":166674,"corporation":false,"usgs":false,"family":"O'Donnell","given":"J.A.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":631628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jorgenson, M.T.","contributorId":26889,"corporation":false,"usgs":true,"family":"Jorgenson","given":"M.T.","affiliations":[],"preferred":false,"id":631629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kanevskiy, M.Z.","contributorId":53603,"corporation":false,"usgs":true,"family":"Kanevskiy","given":"M.Z.","affiliations":[],"preferred":false,"id":631630,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":631631,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shur, Y.","contributorId":29642,"corporation":false,"usgs":true,"family":"Shur","given":"Y.","affiliations":[],"preferred":false,"id":631632,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":631633,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":631625,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70168391,"text":"70168391 - 2015 - The importance of scaling for detecting community patterns: success and failure in assemblages of introduced species","interactions":[],"lastModifiedDate":"2016-08-31T16:00:07","indexId":"70168391","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"The importance of scaling for detecting community patterns: success and failure in assemblages of introduced species","docAbstract":"Community saturation can help to explain why biological invasions fail. However, previous research has documented inconsistent relationships between failed invasions (i.e., an invasive species colonizes but goes extinct) and the number of species present in the invaded community. We use data from bird communities of the Hawaiian island of Oahu, which supports a community of 38 successfully established introduced birds and where 37 species were introduced but went extinct (failed invasions). We develop a modified approach to evaluate the effects of community saturation on invasion failure. Our method accounts (1) for the number of species present (NSP) when the species goes extinct rather than during its introduction; and (2) scaling patterns in bird body mass distributions that accounts for the hierarchical organization of ecosystems and the fact that interaction strength amongst species varies with scale. We found that when using NSP at the time of extinction, NSP was higher for failed introductions as compared to successful introductions, supporting the idea that increasing species richness and putative community saturation mediate invasion resistance. Accounting for scale-specific patterns in body size distributions further improved the relationship between NSP and introduction failure. Results show that a better understanding of invasion outcomes can be obtained when scale-specific community structure is accounted for in the analysis.
","language":"English","publisher":"MDPI","doi":"10.3390/d7030229","usgsCitation":"Allen, C.R., Angeler, D., Moulton, M.P., and Holling, C.S., 2015, The importance of scaling for detecting community patterns: success and failure in assemblages of introduced species: Diversity, v. 7, no. 3, p. 229-241, https://doi.org/10.3390/d7030229.","productDescription":"13 p.","startPage":"229","endPage":"241","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066119","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d7030229","text":"Publisher Index Page"},{"id":317933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Oahu","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", 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G.","affiliations":[],"preferred":false,"id":619881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moulton, Michael P.","contributorId":166723,"corporation":false,"usgs":false,"family":"Moulton","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":619882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holling, Crawford S.","contributorId":20511,"corporation":false,"usgs":true,"family":"Holling","given":"Crawford","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":619883,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70143551,"text":"70143551 - 2015 - Hydroclimatic conditions preceding the March 2014 Oso landslide","interactions":[],"lastModifiedDate":"2015-06-02T11:24:40","indexId":"70143551","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Hydroclimatic conditions preceding the March 2014 Oso landslide","docAbstract":"The 22 March 2014 Oso landslide was one of the deadliest in U.S. history, resulting in 43 fatalities and the destruction of more than 40 structures. We examine synoptic conditions, precipitation records and soil moisture reconstructions in the days, months, and years preceding the landslide. Atmospheric reanalysis shows a period of enhanced moisture transport to the Pacific Northwest beginning on 11 February 2014. The 21- to 42-day periods prior to the landslide had anomalously high precipitation; we estimate that 300-400 mm of precipitation fell at Oso in the 21 days prior to the landslide. Relative only to historical periods ending on 22 March, the return periods of these precipitation accumulations are large (25-88 years). However, relative to the largest accumulations from any time of the year (annual maxima), return periods are more modest (2-6 years). In addition to the 21-42 days prior to the landslide, there is a secondary maximum in the precipitation return periods for the 4 years preceding the landslide. Reconstructed soil moisture was anomalously high prior to the landslide, with a return period that exceeded 40 years about a week before the event.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-15-0008.1","usgsCitation":"Henn, B., Cao, Q., Lettenmaier, D.P., Magirl, C.S., Mass, C., Bower, J.B., St. Laurent, M., Mao, Y., and Perica, S., 2015, Hydroclimatic conditions preceding the March 2014 Oso landslide: Journal of Hydrometeorology, v. 16, no. 3, p. 1243-1249, https://doi.org/10.1175/JHM-D-15-0008.1.","productDescription":"7 p.","startPage":"1243","endPage":"1249","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061638","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":472244,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-15-0008.1","text":"Publisher Index Page"},{"id":298832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.167724609375,\n 47.27177506640826\n ],\n [\n -123.167724609375,\n 48.94415123418794\n ],\n [\n -119.388427734375,\n 48.94415123418794\n ],\n [\n -119.388427734375,\n 47.27177506640826\n ],\n [\n -123.167724609375,\n 47.27177506640826\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"550d44c0e4b02e76d759d87f","contributors":{"authors":[{"text":"Henn, Brian","contributorId":139777,"corporation":false,"usgs":false,"family":"Henn","given":"Brian","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":542793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cao, Qian","contributorId":139778,"corporation":false,"usgs":false,"family":"Cao","given":"Qian","email":"","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":542794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lettenmaier, Dennis P.","contributorId":139779,"corporation":false,"usgs":false,"family":"Lettenmaier","given":"Dennis","email":"","middleInitial":"P.","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":542795,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":542792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mass, Clifford","contributorId":139780,"corporation":false,"usgs":false,"family":"Mass","given":"Clifford","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":542796,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bower, J. Brent","contributorId":138697,"corporation":false,"usgs":false,"family":"Bower","given":"J.","email":"","middleInitial":"Brent","affiliations":[{"id":12498,"text":"NOAA National Weather Service, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":542797,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"St. Laurent, Michael","contributorId":139782,"corporation":false,"usgs":false,"family":"St. Laurent","given":"Michael","email":"","affiliations":[{"id":12907,"text":"NOAA/Hydrometeorological Design Studies Center","active":true,"usgs":false}],"preferred":false,"id":542798,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mao, Yixin","contributorId":139783,"corporation":false,"usgs":false,"family":"Mao","given":"Yixin","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":542799,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Perica, Sanja","contributorId":139784,"corporation":false,"usgs":false,"family":"Perica","given":"Sanja","email":"","affiliations":[{"id":12907,"text":"NOAA/Hydrometeorological Design Studies Center","active":true,"usgs":false}],"preferred":false,"id":542800,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70147405,"text":"70147405 - 2015 - Revisions to some parameters used in stochastic-method simulations of ground motion","interactions":[],"lastModifiedDate":"2015-05-01T10:46:17","indexId":"70147405","displayToPublicDate":"2015-03-01T00:00:00","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":"Revisions to some parameters used in stochastic-method simulations of ground motion","docAbstract":"The stochastic method of ground‐motion simulation specifies the amplitude spectrum as a function of magnitude (M) and distance (R). The manner in which the amplitude spectrum varies with M and R depends on physical‐based parameters that are often constrained by recorded motions for a particular region (e.g., stress parameter, geometrical spreading, quality factor, and crustal amplifications), which we refer to as the seismological model. The remaining ingredient for the stochastic method is the ground‐motion duration. Although the duration obviously affects the character of the ground motion in the time domain, it also significantly affects the response of a single‐degree‐of‐freedom oscillator. Recently published updates to the stochastic method include a new generalized double‐corner‐frequency source model, a new finite‐fault correction, a new parameterization of duration, and a new duration model for active crustal regions. In this article, we augment these updates with a new crustal amplification model and a new duration model for stable continental regions. Random‐vibration theory (RVT) provides a computationally efficient method to compute the peak oscillator response directly from the ground‐motion amplitude spectrum and duration. Because the correction factor used to account for the nonstationarity of the ground motion depends on the ground‐motion amplitude spectrum and duration, we also present new RVT correction factors for both active and stable regions.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120140281","usgsCitation":"Boore, D., and Thompson, E., 2015, Revisions to some parameters used in stochastic-method simulations of ground motion: Bulletin of the Seismological Society of America, v. 105, no. 2A, p. 1029-1041, https://doi.org/10.1785/0120140281.","productDescription":"13 p.","startPage":"1029","endPage":"1041","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061693","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":300018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"2A","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-03","publicationStatus":"PW","scienceBaseUri":"5544a3b6e4b0a658d79478ce","contributors":{"authors":[{"text":"Boore, David 0000-0002-8605-9673 boore@usgs.gov","orcid":"https://orcid.org/0000-0002-8605-9673","contributorId":140502,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":545913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M.","contributorId":79193,"corporation":false,"usgs":false,"family":"Thompson","given":"Eric M.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":545914,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70154798,"text":"70154798 - 2015 - Monitoring and modeling wetland chloride concentrations in relationship to oil and gas development","interactions":[],"lastModifiedDate":"2018-01-05T10:03:54","indexId":"70154798","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring and modeling wetland chloride concentrations in relationship to oil and gas development","docAbstract":"Extraction of oil and gas via unconventional methods is becoming an important aspect of energy production worldwide. Studying the effects of this development in countries where these technologies are being widely used may provide other countries, where development may be proposed, with some insight in terms of concerns associated with development. A fairly recent expansion of unconventional oil and gas development in North America provides such an opportunity. Rapid increases in energy development in North America have caught the attention of managers and scientists as a potential stressor for wildlife and their habitats. Of particular concern in the Northern Great Plains of the U.S. is the potential for chloride-rich produced water associated with unconventional oil and gas development to alter the water chemistry of wetlands. We describe a landscape scale modeling approach designed to examine the relationship between potential chloride contamination in wetlands and patterns of oil and gas development. We used a spatial Bayesian hierarchical modeling approach to assess multiple models explaining chloride concentrations in wetlands. These models included effects related to oil and gas wells (e.g. age of wells, number of wells) and surficial geology (e.g. glacial till, outwash). We found that the model containing the number of wells and the surficial geology surrounding a wetland best explained variation in chloride concentrations. Our spatial predictions showed regions of localized high chloride concentrations. Given the spatiotemporal variability of regional wetland water chemistry, we do not regard our results as predictions of contamination, but rather as a way to identify locations that may require more intensive sampling or further investigation. We suggest that an approach like the one outlined here could easily be extended to more of an adaptive monitoring approach to answer questions about chloride contamination risk that are of interest to managers.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2014.10.028","usgsCitation":"Post van der Burg, M., and Tangen, B., 2015, Monitoring and modeling wetland chloride concentrations in relationship to oil and gas development: Journal of Environmental Management, v. 150, p. 120-127, https://doi.org/10.1016/j.jenvman.2014.10.028.","productDescription":"8 p.","startPage":"120","endPage":"127","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057019","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":306644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","county":"Bottineau County, Burke County, Daniels County, Divide County, McHenry County, Mountrail County, Renville County, Roosevelt County, Sheridan County (MO), Sheridan County (ND), Ward County, Williams County","otherGeospatial":"Bakken Formation, Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.00732421875,\n 48.06339653776211\n ],\n [\n -105.00732421875,\n 48.980216985374994\n ],\n [\n -100.94238281249999,\n 48.980216985374994\n ],\n [\n -100.94238281249999,\n 48.06339653776211\n ],\n [\n -105.00732421875,\n 48.06339653776211\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cdbfb9e4b08400b1fe1419","chorus":{"doi":"10.1016/j.jenvman.2014.10.028","url":"http://dx.doi.org/10.1016/j.jenvman.2014.10.028","publisher":"Elsevier BV","authors":"Post van der Burg Max, Tangen Brian A.","journalName":"Journal of Environmental Management","publicationDate":"3/2015","auditedOn":"1/5/2015"},"contributors":{"authors":[{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":564194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tangen, Brian A. 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":467,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian A.","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":564195,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70173610,"text":"70173610 - 2015 - Modeling risk of pneumonia epizootics in bighorn sheep","interactions":[],"lastModifiedDate":"2016-06-09T15:59:48","indexId":"70173610","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Modeling risk of pneumonia epizootics in bighorn sheep","docAbstract":"Pneumonia epizootics are a major challenge for management of bighorn sheep (Ovis canadensis) affecting persistence of herds, satisfaction of stakeholders, and allocations of resources by management agencies. Risk factors associated with the disease are poorly understood, making pneumonia epizootics hard to predict; such epizootics are thus managed reactively rather than proactively. We developed a model for herds in Montana that identifies risk factors and addresses biological questions about risk. Using Bayesian logistic regression with repeated measures, we found that private land, weed control using domestic sheep or goats, pneumonia history, and herd density were positively associated with risk of pneumonia epizootics in 43 herds that experienced 22 epizootics out of 637 herd-years from 1979–2013. We defined an area of high risk for pathogen exposure as the area of each herd distribution plus a 14.5-km buffer from that boundary. Within this area, the odds of a pneumonia epizootic increased by >1.5 times per additional unit of private land (unit is the standardized % of private land where global ![\"inline](\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.824/asset/equation/jwmg824-math-0001.gif?v=1&t=ip8saaca&s=fdeb51dcf0a30d35ed9230feb228854b91c6cd53\")
= 25.58% and SD = 14.53%). Odds were >3.3 times greater if domestic sheep or goats were used for weed control in a herd's area of high risk. If a herd or its neighbors within the area of high risk had a history of a pneumonia epizootic, odds of a subsequent pneumonia epizootic were >10 times greater. Risk greatly increased when herds were at high density, with nearly 15 times greater odds of a pneumonia epizootic compared to when herds were at low density. Odds of a pneumonia epizootic also appeared to decrease following increased spring precipitation (odds = 0.41 per unit increase, global ![\"inline](\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.824/asset/equation/jwmg824-math-0002.gif?v=1&t=ip8saacb&s=780701fc1c3b1dbbb130e63b3930254bb91f4a97\")
= 100.18% and SD = 26.97%). Risk was not associated with number of federal sheep and goat allotments, proximity to nearest herds of bighorn sheep, ratio of rams to ewes, percentage of average winter precipitation, or whether herds were of native versus mixed or reintroduced origin. We conclude that factors associated with risk of pneumonia epizootics are complex and may not always be from the most obvious sources. The ability to identify high-risk herds will help biologists and managers determine where to focus management efforts and the risk factors that most affect each herd, facilitating more effective, proactive management.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.824","usgsCitation":"Sells, S.N., Mitchell, M.S., Nowak, J.J., Lukacs, P.M., Anderson, N.J., Ramsey, J.M., Gude, J., and Krausman, P.R., 2015, Modeling risk of pneumonia epizootics in bighorn sheep: Journal of Wildlife Management, v. 79, no. 2, p. 195-210, https://doi.org/10.1002/jwmg.824.","productDescription":"16 p.","startPage":"195","endPage":"210","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057280","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"79","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-13","publicationStatus":"PW","scienceBaseUri":"575a9334e4b04f417c275168","contributors":{"authors":[{"text":"Sells, Sarah N.","contributorId":171706,"corporation":false,"usgs":false,"family":"Sells","given":"Sarah","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":638343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowak, J. Joshua","contributorId":171707,"corporation":false,"usgs":false,"family":"Nowak","given":"J.","email":"","middleInitial":"Joshua","affiliations":[],"preferred":false,"id":638344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lukacs, Paul M.","contributorId":101240,"corporation":false,"usgs":true,"family":"Lukacs","given":"Paul","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":638345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Neil J.","contributorId":85870,"corporation":false,"usgs":true,"family":"Anderson","given":"Neil","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ramsey, Jennifer M.","contributorId":88254,"corporation":false,"usgs":true,"family":"Ramsey","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":638347,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gude, Justin A.","contributorId":95780,"corporation":false,"usgs":true,"family":"Gude","given":"Justin A.","affiliations":[],"preferred":false,"id":638348,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Krausman, Paul R.","contributorId":31467,"corporation":false,"usgs":true,"family":"Krausman","given":"Paul","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":638349,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70188042,"text":"70188042 - 2015 - Quantitative attribution of major driving forces on soil organic carbon dynamics","interactions":[],"lastModifiedDate":"2017-05-30T15:55:32","indexId":"70188042","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5407,"text":"Journal of Advances in Modeling Earth Systems","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative attribution of major driving forces on soil organic carbon dynamics","docAbstract":"Soil organic carbon (SOC) storage plays a major role in the global carbon cycle and is affected by many factors including land use/management changes (e.g., biofuel production-oriented changes). However, the contributions of various factors to SOC changes are not well understood and quantified. This study was designed to investigate the impacts of changing farming practices, initial SOC levels, and biological enhancement of grain production on SOC dynamics and to attribute the relative contributions of major driving forces (CO2 enrichment and farming practices) using a fractional factorial modeling design. The case study at a crop site in Iowa in the United States demonstrated that the traditional corn-soybean (CS) rotation could still accumulate SOC over this century (from 4.2 to 6.8 kg C/m2) under the current condition; whereas the continuous-corn (CC) system might have a higher SOC sequestration potential than CS. In either case, however, residue removal could reduce the sink potential substantially. Long-term simulation results also suggested that the equilibrium SOC level may vary greatly (∼5.7 to ∼11 kg C/m2) depending on cropping systems and management practices, and projected growth enhancement could make the magnitudes higher (∼7.8 to ∼13 kg C/m2). Importantly, the factorial design analysis indicated that residue management had the most significant impact (contributing 49.4%) on SOC changes, followed by CO2 Enrichment (37%), Tillage (6.2%), the combination of CO2Enrichment-Residue removal (5.8%), and Fertilization (1.6%). In brief, this study is valuable for understanding the major forces driving SOC dynamics of agroecosystems and informative for decision-makers when seeking the enhancement of SOC sequestration potential and sustainability of biofuel production, especially in the Corn Belt region of the United States.
","language":"English","publisher":"AGU","doi":"10.1002/2014MS000361","usgsCitation":"Wu, Y., Liu, S., and Tan, Z., 2015, Quantitative attribution of major driving forces on soil organic carbon dynamics: Journal of Advances in Modeling Earth Systems, v. 7, no. 1, p. 21-34, https://doi.org/10.1002/2014MS000361.","productDescription":"14 p.","startPage":"21","endPage":"34","ipdsId":"IP-060738","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472241,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014ms000361","text":"Publisher Index Page"},{"id":341881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-16","publicationStatus":"PW","scienceBaseUri":"592e84bde4b092b266f10d4e","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696302,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tan, Zhengxi 0000-0002-4136-0921 ztan@usgs.gov","orcid":"https://orcid.org/0000-0002-4136-0921","contributorId":2945,"corporation":false,"usgs":true,"family":"Tan","given":"Zhengxi","email":"ztan@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696520,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70159362,"text":"70159362 - 2015 - Behavioral responses of freshwater mussels to experimental dewatering","interactions":[],"lastModifiedDate":"2019-12-11T15:52:22","indexId":"70159362","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Behavioral responses of freshwater mussels to experimental dewatering","docAbstract":"Understanding the effects of flow alteration on freshwater ecosystems is critical for predicting species responses and restoring appropriate flow regimes. We experimentally evaluated the effects of 3 dewatering rates on behavior of 6 freshwater mussel species in the context of water-removal rates observed in 21 Atlantic Coast rivers. Horizontal movement differed significantly among species and dewatering rates, but a significant species × dewatering interaction suggested that these factors influence movement in complex ways. Species differences in movement were evident only in controls and under slow dewatering rates, but these differences disappeared at moderate and fast dewatering rates. Burrowing behavior did not differ with respect to species identity or dewatering rate. The proportion of individuals that became stranded did not differ among species, but most individuals became stranded under low and moderate dewatering, and all individuals became stranded under fast dewatering. Mortality after stranding differed strongly among species along a gradient from 25% inPyganodon cataracta to 92% in Alasmidonta marginata. Together, these results suggest that species behavior may differ under gradual dewatering, but all species in our study are poorly adapted for rapid dewatering. Most of the 21 rivers we assessed experienced dewatering events comparable to our moderate rate, and several experienced events comparable to our fast rate. Dewatering events that exceed the movement or survival capability of most mussel species can be expected to result in assemblage-wide impacts. Consequently, the rate of water level change may be important in refining target flow conditions for restoration.
","language":"English","publisher":"Society for Freshwater Science","doi":"10.1086/679446","usgsCitation":"Galbraith, H.S., Blakeslee, C.J., and Lellis, W.A., 2015, Behavioral responses of freshwater mussels to experimental dewatering: Freshwater Science, v. 34, no. 1, p. 42-52, https://doi.org/10.1086/679446.","productDescription":"11 p.","startPage":"42","endPage":"52","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060817","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":310770,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, Pennsylvania","otherGeospatial":"Lake Nessmuk, North Branch Susquehanna River, Paulins Kill River, Pine Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.266357421875,\n 40.38002840251183\n ],\n [\n -75.35522460937499,\n 40.38002840251183\n ],\n [\n -75.35522460937499,\n 42.00032514831621\n ],\n [\n -79.266357421875,\n 42.00032514831621\n ],\n [\n -79.266357421875,\n 40.38002840251183\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5633432ee4b048076347eeb1","contributors":{"authors":[{"text":"Galbraith, Heather S. 0000-0003-3704-3517 hgalbraith@usgs.gov","orcid":"https://orcid.org/0000-0003-3704-3517","contributorId":4519,"corporation":false,"usgs":true,"family":"Galbraith","given":"Heather","email":"hgalbraith@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":578225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakeslee, Carrie J. 0000-0002-0801-5325 cblakeslee@usgs.gov","orcid":"https://orcid.org/0000-0002-0801-5325","contributorId":5462,"corporation":false,"usgs":true,"family":"Blakeslee","given":"Carrie","email":"cblakeslee@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":578226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lellis, William A. 0000-0001-7806-2904 wlellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7806-2904","contributorId":2369,"corporation":false,"usgs":true,"family":"Lellis","given":"William","email":"wlellis@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":578227,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70156880,"text":"70156880 - 2015 - Proposed best modeling practices for assessing the effects of ecosystem restoration on fish","interactions":[],"lastModifiedDate":"2019-07-25T15:05:22","indexId":"70156880","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Proposed best modeling practices for assessing the effects of ecosystem restoration on fish","docAbstract":"Large-scale aquatic ecosystem restoration is increasing and is often controversial because of the economic costs involved, with the focus of the controversies gravitating to the modeling of fish responses. We present a scheme for best practices in selecting, implementing, interpreting, and reporting of fish modeling designed to assess the effects of restoration actions on fish populations and aquatic food webs. Previous best practice schemes that tended to be more general are summarized, and they form the foundation for our scheme that is specifically tailored for fish and restoration. We then present a 31-step scheme, with supporting text and narrative for each step, which goes from understanding how the results will be used through post-auditing to ensure the approach is used effectively in subsequent applications. We also describe 13 concepts that need to be considered in parallel to these best practice steps. Examples of these concepts include: life cycles and strategies; variability and uncertainty; nonequilibrium theory; biological, temporal, and spatial scaling; explicit versus implicit representation of processes; and model validation. These concepts are often not considered or not explicitly stated and casual treatment of them leads to mis-communication and mis-understandings, which in turn, often underlie the resulting controversies. We illustrate a subset of these steps, and their associated concepts, using the three case studies of Glen Canyon Dam on the Colorado River, the wetlands of coastal Louisiana, and the Everglades. Use of our proposed scheme will require investment of additional time and effort (and dollars) to be done effectively. We argue that such an investment is well worth it and will more than pay back in the long run in effective and efficient restoration actions and likely avoided controversies and legal proceedings.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2014.12.020","usgsCitation":"Rose, K.A., Sable, S., DeAngelis, D.L., Yurek, S., Trexler, J.C., Graf, W.L., and Reed, D.J., 2015, Proposed best modeling practices for assessing the effects of ecosystem restoration on fish: Ecological Modelling, v. 300, p. 12-29, https://doi.org/10.1016/j.ecolmodel.2014.12.020.","productDescription":"18 p.","startPage":"12","endPage":"29","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059726","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":307783,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"300","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e6cc37e4b05561fa20a026","contributors":{"authors":[{"text":"Rose, Kenneth A","contributorId":147274,"corporation":false,"usgs":false,"family":"Rose","given":"Kenneth","email":"","middleInitial":"A","affiliations":[{"id":16815,"text":"Dept. of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge","active":true,"usgs":false}],"preferred":false,"id":570954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sable, Shaye","contributorId":147275,"corporation":false,"usgs":false,"family":"Sable","given":"Shaye","affiliations":[{"id":16816,"text":"Dynamic Solutions, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":570955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":147273,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":570953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yurek, Simeon 0000-0002-6209-7915 syurek@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":103167,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","email":"syurek@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":570956,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trexler, Joel C.","contributorId":36267,"corporation":false,"usgs":false,"family":"Trexler","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":570957,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graf, William L.","contributorId":92415,"corporation":false,"usgs":true,"family":"Graf","given":"William","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":570958,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Denise J.","contributorId":71903,"corporation":false,"usgs":true,"family":"Reed","given":"Denise","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":570959,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70156234,"text":"70156234 - 2015 - Equation-free modeling unravels the behavior of complex ecological systems","interactions":[],"lastModifiedDate":"2015-08-19T10:55:00","indexId":"70156234","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Equation-free modeling unravels the behavior of complex ecological systems","docAbstract":"Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.’s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term “equation-free” in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka–Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing “clarity and precision into conjecture” (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.
","language":"English","publisher":"National Academy of Sciences of the United States of America","doi":"10.1073/pnas.1503154112","usgsCitation":"DeAngelis, D., and Yurek, S., 2015, Equation-free modeling unravels the behavior of complex ecological systems: PNAS, v. 112, no. 13, p. 3856-3857, https://doi.org/10.1073/pnas.1503154112.","productDescription":"2 p.","startPage":"3856","endPage":"3857","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063709","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1503154112","text":"Publisher Index Page"},{"id":306924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"13","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-17","publicationStatus":"PW","scienceBaseUri":"55d5a8afe4b0518e3546a4be","chorus":{"doi":"10.1073/pnas.1503154112","url":"http://dx.doi.org/10.1073/pnas.1503154112","publisher":"Proceedings of the National Academy of Sciences","authors":"DeAngelis Donald L., Yurek Simeon","journalName":"Proceedings of the National Academy of Sciences","publicationDate":"3/17/2015"},"contributors":{"authors":[{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":138934,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","email":"don_deangelis@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":568114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yurek, Simeon 0000-0002-6209-7915 syurek@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":103167,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","email":"syurek@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":568568,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70154774,"text":"70154774 - 2015 - Turbidity, light, temperature, and hydropeaking control primary productivity in the Colorado River, Grand Canyon","interactions":[],"lastModifiedDate":"2022-11-14T17:37:39.358873","indexId":"70154774","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Turbidity, light, temperature, and hydropeaking control primary productivity in the Colorado River, Grand Canyon","docAbstract":"Dams and river regulation greatly alter the downstream environment for gross primary production (GPP) because of changes in water clarity, flow, and temperature regimes. We estimated reach-scale GPP in five locations of the regulated Colorado River in Grand Canyon using an open channel model of dissolved oxygen. Benthic GPP dominates in Grand Canyon due to fast transport times and low pelagic algal biomass. In one location, we used a 738 days time series of GPP to identify the relative contribution of different physical controls of GPP. We developed both linear and semimechanistic time series models that account for unmeasured temporal covariance due to factors such as algal biomass dynamics. GPP varied from 0 g O2 m−2 d−1 to 3.0 g O2 m−2 d−1 with a relatively low annual average of 0.8 g O2 m−2 d−1. Semimechanistic models fit the data better than linear models and demonstrated that variation in turbidity primarily controlled GPP. Lower solar insolation during winter and from cloud cover lowered GPP much further. Hydropeaking lowered GPP but only during turbid conditions. Using the best model and parameter values, the model accurately predicted seasonal estimates of GPP at 3 of 4 upriver sites and outperformed the linear model at all sites; discrepancies were likely from higher algal biomass at upstream sites. This modeling approach can predict how changes in physical controls will affect relative rates of GPP throughout the 385 km segment of the Colorado River in Grand Canyon and can be easily applied to other streams and rivers.
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