{"pageNumber":"1199","pageRowStart":"29950","pageSize":"25","recordCount":184937,"records":[{"id":70161741,"text":"70161741 - 2015 - Fire effects on aquatic ecosystems: An assessment of the current state of the science","interactions":[],"lastModifiedDate":"2025-06-25T13:19:04.034953","indexId":"70161741","displayToPublicDate":"2015-12-01T00:00:00","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":"Fire effects on aquatic ecosystems: An assessment of the current state of the science","docAbstract":"<p><span>Fire is a prevalent feature of many landscapes and has numerous and complex effects on geological, hydrological, ecological, and economic systems. In some regions, the frequency and intensity of wildfire have increased in recent years and are projected to escalate with predicted climatic and landuse changes. In addition, prescribed burns continue to be used in many parts of the world to clear vegetation for development projects, encourage desired vegetation, and reduce fuel loads. Given the prevalence of fire on the landscape, authors of papers in this special series examine the complexities of fire as a disturbance shaping freshwater ecosystems and highlight the state of the science. These papers cover key aspects of fire effects that range from vegetation loss and recovery in watersheds to effects on hydrology and water quality with consequences for communities (from algae to fish), food webs, and ecosystem processes (e.g., organic matter subsidies, nutrient cycling) across a range of scales. The results presented in this special series of articles expand our knowledge of fire effects in different biomes, water bodies, and geographic regions, encompassing aquatic population, community, and ecosystem responses. In this overview, we summarize each paper and emphasize its contributions to knowledge on fire ecology and freshwater ecosystems. This overview concludes with a list of 7 research foci that are needed to further our knowledge of fire effects on aquatic ecosystems, including research on: 1) additional biomes and geographic regions; 2) additional habitats, including wetlands and lacustrine ecosystems; 3) different fire severities, sizes, and spatial configurations; and 4) additional response variables (e.g., ecosystem processes) 5) over long (&gt;5 y) time scales 6) with more rigorous study designs and data analyses, and 7) consideration of the effects of fire management practices and policies on aquatic ecosystems.</span></p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/684073","usgsCitation":"Bixby, R.J., Cooper, S., Gresswell, R.E., Brown, L.E., Dahm, C.N., and Dwire, K.A., 2015, Fire effects on aquatic ecosystems: An assessment of the current state of the science: Freshwater Science, v. 34, no. 4, p. 1340-1350, https://doi.org/10.1086/684073.","productDescription":"11 p.","startPage":"1340","endPage":"1350","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068454","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471611,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/5q9165nf","text":"External Repository"},{"id":381478,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568cf741e4b0e7a44bc0f156","contributors":{"authors":[{"text":"Bixby, Rebecca J.","contributorId":147389,"corporation":false,"usgs":false,"family":"Bixby","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":16834,"text":"Dept. of Biology and Museum of Southwestern Biology, Univ of NM","active":true,"usgs":false}],"preferred":false,"id":807071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooper, Scott D.","contributorId":152035,"corporation":false,"usgs":false,"family":"Cooper","given":"Scott D.","affiliations":[{"id":18860,"text":"Department of Ecology, Evolution, and Marine Biology and Marine Science Institute      University of California","active":true,"usgs":false}],"preferred":false,"id":807072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":152031,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":587615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Lee E.","contributorId":152036,"corporation":false,"usgs":false,"family":"Brown","given":"Lee","email":"","middleInitial":"E.","affiliations":[{"id":18861,"text":"School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":807073,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahm, Clifford N.","contributorId":152037,"corporation":false,"usgs":false,"family":"Dahm","given":"Clifford","email":"","middleInitial":"N.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":587619,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dwire, Kathleen A.","contributorId":225615,"corporation":false,"usgs":false,"family":"Dwire","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[{"id":41171,"text":"US Forest Service, Rocky Mountain Research Station, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":807075,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70193797,"text":"70193797 - 2015 - Determining climate change management priorities: A case study from Wisconsin ","interactions":[],"lastModifiedDate":"2017-11-10T10:32:00","indexId":"70193797","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2231,"text":"Journal of Conservation Planning","active":true,"publicationSubtype":{"id":10}},"title":"Determining climate change management priorities: A case study from Wisconsin ","docAbstract":"<p>A burgeoning dialogue exists regarding how to allocate resources to maximize the likelihood of long-term biodiversity conservation within the context of climate change. To make effective decisions in natural resource management, an iterative, collaborative, and learning-based decision process may be more successful than a strictly consultative approach. One important, early step in a decision process is to identify priority species or systems. Although this promotes the conservation of select species or systems, it may inadvertently alter the future of non-target species and systems. We describe a process to screen terrestrial wildlife for potential sensitivity to climate change and then use the results to engage natural resource professionals in a process of identifying priorities for monitoring, research, and adaptation strategy implementation. We demonstrate this approach using a case study from Wisconsin. In Wisconsin, experts identified 23 out of 353 species with sufficient empirical research and management understanding to inform targeted action. Habitat management and management of hydrological conditions were the common strategies for targeted action. Although there may be an interest in adaptation strategy implementation for many species and systems, experts considered existing information inadequate to inform targeted action. According to experts, 40% of the vertebrate species in Wisconsin will require near-term intervention for climate adaptation. These results will inform state-wide conservation planning as well as regional efforts. </p>","language":"English","publisher":"The Conservation Fund","usgsCitation":"LeDee, O., and Ribic, C., 2015, Determining climate change management priorities: A case study from Wisconsin : Journal of Conservation Planning, v. 11, no. 1, p. 1-12.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-040823","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":348216,"type":{"id":15,"text":"Index Page"},"url":"https://www.journalconsplanning.org/"}],"country":"United 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,{"id":70184233,"text":"70184233 - 2015 - The 2014 update to the National Seismic Hazard Model in California","interactions":[],"lastModifiedDate":"2017-03-06T10:50:05","indexId":"70184233","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2014 update to the National Seismic Hazard Model in California","docAbstract":"<p><span>The 2014 update to the U. S. Geological Survey National Seismic Hazard Model in California introduces a new earthquake rate model and new ground motion models (GMMs) that give rise to numerous changes to seismic hazard throughout the state. The updated earthquake rate model is the third version of the Uniform California Earthquake Rupture Forecast (UCERF3), wherein the rates of all ruptures are determined via a self-consistent inverse methodology. This approach accommodates multifault ruptures and reduces the overprediction of moderate earthquake rates exhibited by the previous model (UCERF2). UCERF3 introduces new faults, changes to slip or moment rates on existing faults, and adaptively smoothed gridded seismicity source models, all of which contribute to significant changes in hazard. New GMMs increase ground motion near large strike-slip faults and reduce hazard over dip-slip faults. The addition of very large strike-slip ruptures and decreased reverse fault rupture rates in UCERF3 further enhances these effects.</span></p>","language":"English","publisher":"EERI","doi":"10.1193/110314EQS176M","usgsCitation":"Powers, P.M., and Field, E.H., 2015, The 2014 update to the National Seismic Hazard Model in California: Earthquake Spectra, v. 31, no. S1, p. 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,{"id":70184232,"text":"70184232 - 2015 - Hydrologic implications of GRACE satellite data in the Colorado River Basin","interactions":[],"lastModifiedDate":"2018-01-30T18:44:55","indexId":"70184232","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic implications of GRACE satellite data in the Colorado River Basin","docAbstract":"<p><span>Use of GRACE (Gravity Recovery and Climate Experiment) satellites for assessing global water resources is rapidly expanding. Here we advance application of GRACE satellites by reconstructing long-term total water storage (TWS) changes from ground-based monitoring and modeling data. We applied the approach to the Colorado River Basin which has experienced multiyear intense droughts at decadal intervals. Estimated TWS declined by 94 km</span><sup>3</sup><span> during 1986–1990 and by 102 km</span><sup>3</sup><span> during 1998–2004, similar to the TWS depletion recorded by GRACE (47 km</span><sup>3</sup><span>) during 2010–2013. Our analysis indicates that TWS depletion is dominated by reductions in surface reservoir and soil moisture storage in the upper Colorado basin with additional reductions in groundwater storage in the lower basin. Groundwater storage changes are controlled mostly by natural responses to wet and dry cycles and irrigation pumping outside of Colorado River delivery zones based on ground-based water level and gravity data. Water storage changes are controlled primarily by variable water inputs in response to wet and dry cycles rather than increasing water use. Surface reservoir storage buffers supply variability with current reservoir storage representing ∼2.5 years of available water use. This study can be used as a template showing how to extend short-term GRACE TWS records and using all available data on storage components of TWS to interpret GRACE data, especially within the context of droughts.</span></p>","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR018090","usgsCitation":"Scanlon, B., Zhang, Z., Reedy, R.C., Pool, D.R., Save, H., Long, D., Chen, J., Wolock, D.M., Conway, B.D., and Winester, D., 2015, Hydrologic implications of GRACE satellite data in the Colorado River Basin: Water Resources Research, v. 51, no. 12, p. 9891-9903, https://doi.org/10.1002/2015WR018090.","productDescription":"13 p.","startPage":"9891","endPage":"9903","ipdsId":"IP-070650","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":471613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018090","text":"Publisher Index Page"},{"id":336855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Colorado River Basin","volume":"51","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-24","publicationStatus":"PW","scienceBaseUri":"58be833ce4b014cc3a3a99f3","contributors":{"authors":[{"text":"Scanlon, Bridget R.","contributorId":74093,"corporation":false,"usgs":true,"family":"Scanlon","given":"Bridget R.","affiliations":[],"preferred":false,"id":680670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Zizhan","contributorId":187508,"corporation":false,"usgs":false,"family":"Zhang","given":"Zizhan","email":"","affiliations":[],"preferred":false,"id":680671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reedy, Robert C.","contributorId":187509,"corporation":false,"usgs":false,"family":"Reedy","given":"Robert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":680672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pool, Donald R. drpool@usgs.gov","contributorId":1121,"corporation":false,"usgs":true,"family":"Pool","given":"Donald","email":"drpool@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Save, Himanshu","contributorId":187510,"corporation":false,"usgs":false,"family":"Save","given":"Himanshu","email":"","affiliations":[],"preferred":false,"id":680673,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, Di","contributorId":187511,"corporation":false,"usgs":false,"family":"Long","given":"Di","email":"","affiliations":[],"preferred":false,"id":680674,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chen, Jianli","contributorId":187512,"corporation":false,"usgs":false,"family":"Chen","given":"Jianli","email":"","affiliations":[],"preferred":false,"id":680675,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":680676,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conway, Brian D.","contributorId":187513,"corporation":false,"usgs":false,"family":"Conway","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":680677,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Winester, Daniel","contributorId":187514,"corporation":false,"usgs":false,"family":"Winester","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":680678,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70184229,"text":"70184229 - 2015 - The 2014 United States National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2017-03-06T10:59:13","indexId":"70184229","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2014 United States National Seismic Hazard Model","docAbstract":"<p><span>New seismic hazard maps have been developed for the conterminous United States using the latest data, models, and methods available for assessing earthquake hazard. The hazard models incorporate new information on earthquake rupture behavior observed in recent earthquakes; fault studies that use both geologic and geodetic strain rate data; earthquake catalogs through 2012 that include new assessments of locations and magnitudes; earthquake adaptive smoothing models that more fully account for the spatial clustering of earthquakes; and 22 ground motion models, some of which consider more than double the shaking data applied previously. Alternative input models account for larger earthquakes, more complicated ruptures, and more varied ground shaking estimates than assumed in earlier models. The ground motions, for levels applied in building codes, differ from the previous version by less than ±10% over 60% of the country, but can differ by ±50% in localized areas. The models are incorporated in insurance rates, risk assessments, and as input into the U.S. building code provisions for earthquake ground shaking.</span></p>","language":"English","publisher":"EERI","doi":"10.1193/120814EQS210M","usgsCitation":"Petersen, M.D., Moschetti, M.P., Powers, P.M., Mueller, C., Haller, K., Frankel, A.D., Zeng, Y., Rezaeian, S., Harmsen, S., Boyd, O.S., Field, E., Chen, R., Rukstales, K.S., Luco, N., Wheeler, R., Williams, R., and Olsen, A.H., 2015, The 2014 United States National Seismic Hazard Model: Earthquake Spectra, v. 31, no. S!, p. S1-S30, https://doi.org/10.1193/120814EQS210M.","productDescription":"30 p.","startPage":"S1","endPage":"S30","ipdsId":"IP-066439","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":336857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"S!","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"58be833ce4b014cc3a3a99f7","contributors":{"authors":[{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science 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,{"id":70160135,"text":"70160135 - 2015 - Natural and unnatural oil slicks in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2016-02-01T13:31:39","indexId":"70160135","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Natural and unnatural oil slicks in the Gulf of Mexico","docAbstract":"<p><span>When wind speeds are 2 &ndash; 10 m s</span><span>&minus;1</span><span>, reflective contrasts in the ocean surface make oil slicks visible to synthetic aperture radar (SAR) under all sky conditions. Neural network analysis of satellite SAR images quantified the magnitude and distribution of surface oil in the Gulf of Mexico from persistent, natural seeps and from the Deepwater Horizon (DWH) discharge. This analysis identified 914 natural oil seep zones across the entire Gulf of Mexico in pre-2010 data. Their &sim;0.1 &micro;m slicks covered an aggregated average of 775 km</span><span>2</span><span>. Assuming an average volume of 77.5 m</span><span>3</span><span>over an 8 &ndash; 24 h lifespan per oil slick, the floating oil indicates a surface flux of 2.5 &ndash; 9.4 &times; 10</span><span>4</span><span>&nbsp;m</span><span>3</span><span>&nbsp;y</span><span>&minus;1</span><span>. Oil from natural slicks was regionally concentrated: 68%, 25%, 7%, and &lt;1% of the total was observed in the NW, SW, NE and SE Gulf, respectively. This reflects differences in basin history and hydrocarbon generation. SAR images from 2010 showed that the 87-day DWH discharge produced a surface-oil footprint fundamentally different from background seepage, with an average ocean area of 11,200 km</span><span>2</span><span>&nbsp;(SD 5,028) and a volume of 22,600 m</span><span>3</span><span>&nbsp;(SD 5,411). Peak magnitudes of oil were detected during equivalent, &sim;14-day intervals around 23 May and 18 June, when wind speeds remained &lt;5 m s</span><span>&minus;1</span><span>. Over this interval, aggregated volume of floating oil decreased by 21%; area covered increased by 49% (</span><i>p</i><span>&thinsp;&lt;&thinsp;.1), potentially altering its ecological impact. The most likely causes were increased applications of dispersant and surface burning operations.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/2015JC011062","collaboration":"Florida State University, Woods Hole Oceanographic Institution, NOAA, RPS ASA, Univ. of Southern Florida, Bubbleology Research International, Stratus Consulting","usgsCitation":"MacDonald, I.R., O. Garcia-Pineda, Beet, A., Asl, S.D., Feng, L., Graettinger, D.G., French-McCay, D., Holmes, J., C. Hu, F. Huffer, I. Leifer, Mueller-Karger, F., Solow, A., Silva, M., and Swayze, G.A., 2015, Natural and unnatural oil slicks in the Gulf of Mexico: Journal of Geophysical Research C: Oceans, v. 120, no. 12, p. 8364-8380, https://doi.org/10.1002/2015JC011062.","productDescription":"15 p.","startPage":"8364","endPage":"8380","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063451","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":471615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jc011062","text":"Publisher Index Page"},{"id":312210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.650390625,\n              24.647017162630366\n            ],\n            [\n              -85.0341796875,\n              22.471954507739227\n            ],\n            [\n              -87.4951171875,\n              21.69826549685252\n            ],\n            [\n              -90,\n              21.493963563064455\n            ],\n            [\n              -90.791015625,\n              20.756113874762082\n            ],\n            [\n              -90.703125,\n              19.766703551716976\n            ],\n            [\n              -91.845703125,\n              18.812717856407776\n            ],\n            [\n              -94.52636718749999,\n              18.35452552912664\n            ],\n            [\n              -96.85546875,\n              20.673905264672843\n            ],\n            [\n              -97.8662109375,\n              22.87744046489713\n            ],\n            [\n              -97.3388671875,\n              25.958044673317843\n            ],\n            [\n              -97.2509765625,\n              27.449790329784214\n            ],\n            [\n              -96.0205078125,\n              28.729130483430154\n            ],\n            [\n              -94.04296874999999,\n              29.611670115197377\n            ],\n            [\n              -91.7138671875,\n              29.611670115197377\n            ],\n            [\n              -89.47265625,\n              28.8831596093235\n            ],\n            [\n              -88.76953125,\n              29.113775395114416\n            ],\n            [\n              -89.2529296875,\n              29.76437737516313\n            ],\n            [\n              -89.07714843749999,\n              30.031055426540206\n            ],\n            [\n              -88.6376953125,\n              30.372875188118016\n            ],\n            [\n              -86.8798828125,\n              30.221101852485987\n            ],\n            [\n              -84.814453125,\n              29.6880527498568\n            ],\n            [\n              -83.84765625,\n              29.76437737516313\n            ],\n            [\n              -83.0126953125,\n              28.536274512989916\n            ],\n            [\n              -82.4853515625,\n              27.0982539061379\n            ],\n            [\n              -81.474609375,\n              25.363882272740256\n            ],\n            [\n              -80.85937499999999,\n              25.045792240303445\n            ],\n            [\n              -81.650390625,\n              24.647017162630366\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"120","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-28","publicationStatus":"PW","scienceBaseUri":"566c01ece4b09cfe53ca5af4","contributors":{"authors":[{"text":"MacDonald, Ian R.","contributorId":150517,"corporation":false,"usgs":false,"family":"MacDonald","given":"Ian","email":"","middleInitial":"R.","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":582005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O. 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Hu","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":582011,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"F. Huffer","contributorId":150524,"corporation":false,"usgs":false,"family":"F. Huffer","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":582012,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"I. Leifer","contributorId":150525,"corporation":false,"usgs":false,"family":"I. Leifer","affiliations":[{"id":18044,"text":"Bubbleology Research International","active":true,"usgs":false}],"preferred":false,"id":582013,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mueller-Karger, F.","contributorId":150526,"corporation":false,"usgs":false,"family":"Mueller-Karger","given":"F.","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":582014,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Solow, A.","contributorId":150527,"corporation":false,"usgs":false,"family":"Solow","given":"A.","email":"","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":582015,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Silva, M.","contributorId":150530,"corporation":false,"usgs":false,"family":"Silva","given":"M.","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":582018,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Swayze, Gregg A. 0000-0002-1814-7823 gswayze@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7823","contributorId":518,"corporation":false,"usgs":true,"family":"Swayze","given":"Gregg","email":"gswayze@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":582004,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70189525,"text":"70189525 - 2015 - Removal of terrestrial DOC in aquatic ecosystems of a temperate river network","interactions":[],"lastModifiedDate":"2017-07-14T12:24:34","indexId":"70189525","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Removal of terrestrial DOC in aquatic ecosystems of a temperate river network","docAbstract":"<div class=\"article-section__content mainAbstract\"><p>Surface waters play a potentially important role in the global carbon balance. Dissolved organic carbon (DOC) fluxes are a major transfer of terrestrial carbon to river systems, and the fate of DOC in aquatic systems is poorly constrained. We used a unique combination of spatially distributed sampling of three DOC fractions throughout a river network and modeling to quantify the net removal of terrestrial DOC during a summer base flow period. We found that aquatic reactivity of terrestrial DOC leading to net loss is low, closer to conservative chloride than to reactive nitrogen. Net removal occurred mainly from the hydrophobic organic acid fraction, while hydrophilic and transphilic acids showed no net change, indicating that partitioning of bulk DOC into different fractions is critical for understanding terrestrial DOC removal. These findings suggest that river systems may have only a modest ability to alter the amounts of terrestrial DOC delivered to coastal zones.</p></div>","language":"English","publisher":"AGU","doi":"10.1002/2015GL064647","usgsCitation":"Wollheim, W.M., Stewart, R.J., Aiken, G.R., Butler, K.D., Morse, N.B., and Salisbury, J., 2015, Removal of terrestrial DOC in aquatic ecosystems of a temperate river network: Geophysical Research Letters, v. 42, no. 16, p. 6671-6679, https://doi.org/10.1002/2015GL064647.","productDescription":"9 p.","startPage":"6671","endPage":"6679","ipdsId":"IP-064250","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471609,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl064647","text":"Publisher Index Page"},{"id":343869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Ipswich River","volume":"42","issue":"16","noUsgsAuthors":false,"publicationDate":"2015-08-19","publicationStatus":"PW","scienceBaseUri":"5969d82ce4b0d1f9f060a191","contributors":{"authors":[{"text":"Wollheim, W. M.","contributorId":10912,"corporation":false,"usgs":false,"family":"Wollheim","given":"W.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":705035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, R. J.","contributorId":194685,"corporation":false,"usgs":false,"family":"Stewart","given":"R.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":705036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":705037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butler, Kenna D. kebutler@usgs.gov","contributorId":3283,"corporation":false,"usgs":true,"family":"Butler","given":"Kenna","email":"kebutler@usgs.gov","middleInitial":"D.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":705038,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morse, Nathaniel B.","contributorId":139747,"corporation":false,"usgs":false,"family":"Morse","given":"Nathaniel","email":"","middleInitial":"B.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":705039,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Salisbury, J.","contributorId":194686,"corporation":false,"usgs":false,"family":"Salisbury","given":"J.","affiliations":[],"preferred":false,"id":705040,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70159330,"text":"70159330 - 2015 - Gopherus agassizii (Agassiz's Desert Tortoise).  Attempted predation.","interactions":[],"lastModifiedDate":"2016-09-22T10:35:35","indexId":"70159330","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"Gopherus agassizii (Agassiz's Desert Tortoise).  Attempted predation.","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"Herpetological Review","usgsCitation":"Spenceley, A., Mack, J.S., and Berry, K.H., 2015, Gopherus agassizii (Agassiz's Desert Tortoise).  Attempted predation.: Herpetological Review, v. 46, no. 3, p. 422-423.","productDescription":"2 p.","startPage":"422","endPage":"423","ipdsId":"IP-065571","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":328854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7ee36e4b0bc0bec09e909","contributors":{"authors":[{"text":"Spenceley, Ashley","contributorId":149345,"corporation":false,"usgs":false,"family":"Spenceley","given":"Ashley","email":"","affiliations":[{"id":17713,"text":"formerly with WERC, USGS","active":true,"usgs":false}],"preferred":false,"id":578032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mack, Jeremy S. jmack@usgs.gov","contributorId":3851,"corporation":false,"usgs":true,"family":"Mack","given":"Jeremy","email":"jmack@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":578033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":578031,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70160354,"text":"70160354 - 2015 - Tidal marsh susceptibility to sea-level rise: importance of local-scale models","interactions":[],"lastModifiedDate":"2017-07-19T15:43:12","indexId":"70160354","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Tidal marsh susceptibility to sea-level rise: importance of local-scale models","docAbstract":"<p>Increasing concern over sea-level rise impacts to coastal tidal marsh ecosystems has led to modeling efforts to anticipate outcomes for resource management decision making. Few studies on the Pacific coast of North America have modeled sea-level rise marsh susceptibility at a scale relevant to local wildlife populations and plant communities. Here, we use a novel approach in developing an empirical sea-level rise ecological response model that can be applied to key management questions. Calculated elevation change over 13 y for a 324-ha portion of San Pablo Bay National Wildlife Refuge, California, USA, was used to represent local accretion and subsidence processes. Next, we coupled detailed plant community and elevation surveys with measured rates of inundation frequency to model marsh state changes to 2100. By grouping plant communities into low, mid, and high marsh habitats, we were able to assess wildlife species vulnerability and to better understand outcomes for habitat resiliency. Starting study-site conditions were comprised of 78% (253-ha) high marsh, 7% (30-ha) mid marsh, and 4% (18-ha) low marsh habitats, dominated by pickleweed <i>Sarcocornia pacifica</i> and cordgrass <i>Spartina</i> spp. Only under the low sea-level rise scenario (44 cm by 2100) did our models show persistence of some marsh habitats to 2100, with the area dominated by low marsh habitats. Under mid (93 cm by 2100) and high sea-level rise scenarios (166 cm by 2100), most mid and high marsh habitat was lost by 2070, with only 15% (65 ha) remaining, and a complete loss of these habitats by 2080. Low marsh habitat increased temporarily under all three sea-level rise scenarios, with the peak (286 ha) in 2070, adding habitat for the endemic endangered California Ridgway&rsquo;s rail <i>Rallus obsoletus obsoletus</i>. Under mid and high sea-level rise scenarios, an almost complete conversion to mudflat occurred, with most of the area below mean sea level. Our modeling assumed no marsh migration upslope due to human levee and infrastructure preventing these types of processes. Other modeling efforts done for this area have projected marsh persistence to 2100, but our modeling effort with site-specific datasets allowed us to model at a finer resolution with much higher local confidence, resulting in different results for management. Our results suggest that projected sea-level rise will have significant impacts on marsh plant communities and obligate wildlife, including those already under federal and state protection. Comprehensive modeling as done here improves the potential to implement adaptive management strategies and prevent marsh habitat and wildlife loss in the future.</p>","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington D.C.","doi":"10.3996/062014-JFWM-048","usgsCitation":"Thorne, K.M., Buffington, K., Elliott-Fisk, D., and Takekawa, J.Y., 2015, Tidal marsh susceptibility to sea-level rise: importance of local-scale models: Journal of Fish and Wildlife Management, v. 3, no. 2, p. 290-304, https://doi.org/10.3996/062014-JFWM-048.","productDescription":"15 p.","startPage":"290","endPage":"304","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063637","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488825,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/062014-jfwm-048","text":"Publisher Index 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,{"id":70160353,"text":"70160353 - 2015 - Strong-motion observations of the M 7.8 Gorkha, Nepal, earthquake sequence and development of the N-shake strong-motion network","interactions":[],"lastModifiedDate":"2018-10-24T16:48:39","indexId":"70160353","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Strong-motion observations of the M 7.8 Gorkha, Nepal, earthquake sequence and development of the N-shake strong-motion network","docAbstract":"<p>We present and describe strong-motion data observations from the 2015 M 7.8 Gorkha, Nepal, earthquake sequence collected using existing and new Quake-Catcher Network (QCN) and U.S. Geological Survey NetQuakes sensors located in the Kathmandu Valley. A comparison of QCN data with waveforms recorded by a conventional strong-motion (NetQuakes) instrument validates the QCN data. We present preliminary analysis of spectral accelerations, and peak ground acceleration and velocity for earthquakes up to M 7.3 from the QCN stations, as well as preliminary analysis of the mainshock recording from the NetQuakes station. We show that mainshock peak accelerations were lower than expected and conclude the Kathmandu Valley experienced a pervasively nonlinear response during the mainshock. Phase picks from the QCN and NetQuakes data are also used to improve aftershock locations. This study confirms the utility of QCN instruments to contribute to ground-motion investigations and aftershock response in regions where conventional instrumentation and open-access seismic data are limited. Initial pilot installations of QCN instruments in 2014 are now being expanded to create the Nepal&ndash;Shaking Hazard Assessment for Kathmandu and its Environment (N-SHAKE) network.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220150146","usgsCitation":"Dixit, A., Ringler, A.T., Sumy, D.F., Cochran, E.S., Hough, S.E., Martin, S., Gibbons, S., Luetgert, J.H., Galetzka, J., Shrestha, S., Rajaure, S., and McNamara, D.E., 2015, Strong-motion observations of the M 7.8 Gorkha, Nepal, earthquake sequence and development of the N-shake strong-motion network: Seismological Research Letters, v. 86, no. 6, p. 1533-1539, https://doi.org/10.1785/0220150146.","productDescription":"7 p.","startPage":"1533","endPage":"1539","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066938","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471599,"rank":0,"type":{"id":41,"text":"Open Access External 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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":582720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sumy, Danielle F.","contributorId":108025,"corporation":false,"usgs":true,"family":"Sumy","given":"Danielle","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":582721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":582722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":582723,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, Stacey","contributorId":35165,"corporation":false,"usgs":false,"family":"Martin","given":"Stacey","affiliations":[{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":582724,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gibbons, Steven","contributorId":150709,"corporation":false,"usgs":false,"family":"Gibbons","given":"Steven","affiliations":[{"id":18074,"text":"NORSAR","active":true,"usgs":false}],"preferred":false,"id":582725,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Luetgert, James H. luetgert@usgs.gov","contributorId":4203,"corporation":false,"usgs":true,"family":"Luetgert","given":"James","email":"luetgert@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":582726,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Galetzka, John","contributorId":147535,"corporation":false,"usgs":false,"family":"Galetzka","given":"John","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":582727,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shrestha, Surya","contributorId":150710,"corporation":false,"usgs":false,"family":"Shrestha","given":"Surya","email":"","affiliations":[{"id":18073,"text":"National Society for Earthquake Technology","active":true,"usgs":false}],"preferred":false,"id":582728,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rajaure, Sudhir","contributorId":150711,"corporation":false,"usgs":false,"family":"Rajaure","given":"Sudhir","email":"","affiliations":[{"id":18073,"text":"National Society for Earthquake Technology","active":true,"usgs":false}],"preferred":false,"id":582729,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":582730,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70187762,"text":"70187762 - 2015 - Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products","interactions":[],"lastModifiedDate":"2017-05-17T11:19:03","indexId":"70187762","displayToPublicDate":"2015-12-01T00:00:00","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":"Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products","docAbstract":"<p><span>There is a high demand for agrohydrologic models to use gridded near-surface air temperature data as the model input for estimating regional and global water budgets and cycles. The Global Land Data Assimilation System (GLDAS) developed by combining simulation models with observations provides a long-term gridded meteorological dataset at the global scale. However, the GLDAS air temperature products have not been comprehensively evaluated, although the accuracy of the products was assessed in limited areas. In this study, the daily 0.25° resolution GLDAS air temperature data are compared with two reference datasets: 1) 1-km-resolution gridded Daymet data (2002 and 2010) for the conterminous United States and 2) global meteorological observations (2000–11) archived from the Global Historical Climatology Network (GHCN). The comparison of the GLDAS datasets with the GHCN datasets, including 13 511 weather stations, indicates a fairly high accuracy of the GLDAS data for daily temperature. The quality of the GLDAS air temperature data, however, is not always consistent in different regions of the world; for example, some areas in Africa and South America show relatively low accuracy. Spatial and temporal analyses reveal a high agreement between GLDAS and Daymet daily air temperature datasets, although spatial details in high mountainous areas are not sufficiently estimated by the GLDAS data. The evaluation of the GLDAS data demonstrates that the air temperature estimates are generally accurate, but caution should be taken when the data are used in mountainous areas or places with sparse weather stations.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-14-0230.1","usgsCitation":"Ji, L., Senay, G.B., and Verdin, J.P., 2015, Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products: Journal of Hydrometeorology, v. 16, p. 2463-2480, https://doi.org/10.1175/JHM-D-14-0230.1.","productDescription":"18 p.","startPage":"2463","endPage":"2480","ipdsId":"IP-060871","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471619,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-14-0230.1","text":"Publisher Index Page"},{"id":341434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","noUsgsAuthors":false,"publicationDate":"2015-11-17","publicationStatus":"PW","scienceBaseUri":"593e26a5e4b0764e6c61b754","contributors":{"authors":[{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":139587,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":695522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":695524,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196071,"text":"70196071 - 2015 - Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling","interactions":[],"lastModifiedDate":"2018-09-13T16:50:34","indexId":"70196071","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling","docAbstract":"<p><span>The SPARROW (SPAtially Referenced Regression on Watershed attributes) model was used to simulate annual phosphorus loads and concentrations in unmonitored stream reaches in California, U.S., and portions of Nevada and Oregon. The model was calibrated using de-trended streamflow and phosphorus concentration data at 80 locations. The model explained 91% of the variability in loads and 51% of the variability in yields for a base year of 2002. Point sources, geological background, and cultivated land were significant sources. Variables used to explain delivery of phosphorus from land to water were precipitation and soil clay content. Aquatic loss of phosphorus was significant in streams of all sizes, with the greatest decay predicted in small- and intermediate-sized streams. Geological sources, including volcanic rocks and shales, were the principal control on concentrations and loads in many regions. Some localized formations such as the Monterey shale of southern California are important sources of phosphorus and may contribute to elevated stream concentrations. Many of the larger point source facilities were located in downstream areas, near the ocean, and do not affect inland streams except for a few locations. Large areas of cultivated land result in phosphorus load increases, but do not necessarily increase the loads above those of geological background in some cases because of local hydrology, which limits the potential of phosphorus transport from land to streams.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12326","usgsCitation":"Domagalski, J.L., and Saleh, D., 2015, Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling: Journal of the American Water Resources Association, v. 51, no. 6, p. 1463-1486, https://doi.org/10.1111/1752-1688.12326.","productDescription":"24 p.","startPage":"1463","endPage":"1486","ipdsId":"IP-052538","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":352579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"6","noUsgsAuthors":false,"publicationDate":"2015-07-14","publicationStatus":"PW","scienceBaseUri":"5afeeb20e4b0da30c1bfc64a","contributors":{"authors":[{"text":"Domagalski, Joseph L. 0000-0002-6032-757X joed@usgs.gov","orcid":"https://orcid.org/0000-0002-6032-757X","contributorId":1330,"corporation":false,"usgs":true,"family":"Domagalski","given":"Joseph","email":"joed@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saleh, Dina 0000-0002-1406-9303 dsaleh@usgs.gov","orcid":"https://orcid.org/0000-0002-1406-9303","contributorId":939,"corporation":false,"usgs":true,"family":"Saleh","given":"Dina","email":"dsaleh@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731208,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192077,"text":"70192077 - 2015 - The nest-concealment hypothesis: New insights from a comparative analysis","interactions":[],"lastModifiedDate":"2017-10-26T13:50:36","indexId":"70192077","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"The nest-concealment hypothesis: New insights from a comparative analysis","docAbstract":"<p><span>Selection of a breeding site is critical for many animals, especially for birds whose offspring are stationary during development. Thus, birds are often assumed to prefer concealed nest sites. However, 74% of studies (</span><i>n</i><span><span>&nbsp;</span>= 106) that have evaluated this relationship for open-cup nesting songbirds in North America failed to support the nest-concealment hypothesis. We conducted a comparative analysis to identify factors that contribute to variation in the ability of researchers to find support for the nest-concealment hypothesis. We found that some of the discrepancy among studies can be explained by interspecific differences in morphological and extrinsic factors that affect nest predation. Moreover, methods that investigators used to estimate concealment affected whether studies found support for the nest-concealment hypothesis; 33% of the studies that used quantitative estimates found support for the nest-concealment hypothesis whereas only 10% of the studies that used qualitative estimates found support. The timing of measurements also explained some of the ambiguity; studies that provided little information regarding the timing of their foliage density estimates were less likely to support the nest-concealment hypothesis. Species with more conspicuous male plumage were less likely to support the nest-concealment hypothesis when we analyzed studies that used visual estimates. Whereas species with more conspicuous female plumage were more likely to support the nest-concealment hypothesis when we analyzed studies that used quantitative measures. Our results demonstrate that support for the nest-concealment hypothesis has been equivocal, but that some of the ambiguity can be explained by morphological traits and methods used to measure concealment.</span></p>","language":"English","publisher":"The Wilson Ornithological Society","doi":"10.1676/14-162.1","usgsCitation":"Borgmann, K.L., and Conway, C.J., 2015, The nest-concealment hypothesis: New insights from a comparative analysis: Wilson Journal of Ornithology, v. 127, no. 4, p. 646-660, https://doi.org/10.1676/14-162.1.","productDescription":"15 p.","startPage":"646","endPage":"660","ipdsId":"IP-056235","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":347480,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07eb2ae4b09af898c8ccc2","contributors":{"authors":[{"text":"Borgmann, Kathi L.","contributorId":171647,"corporation":false,"usgs":false,"family":"Borgmann","given":"Kathi","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":716418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714091,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191099,"text":"70191099 - 2015 - Combining NLCD and MODIS to create a land cover-albedo database for the continental United States","interactions":[],"lastModifiedDate":"2017-09-26T14:06:20","indexId":"70191099","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Combining NLCD and MODIS to create a land cover-albedo database for the continental United States","docAbstract":"<p><span>Land surface albedo is an essential climate variable that is tightly linked to land cover, such that specific land cover classes (e.g., deciduous broadleaf forest, cropland) have characteristic albedos. Despite the normative of land-cover class specific albedos, there is considerable variability in albedo within a land cover class. The National Land Cover Database (NLCD) and the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo product were combined to produce a long-term (14&nbsp;years) integrated land cover-albedo database for the continental United States that can be used to examine the temporal behavior of albedo as a function of land cover. The integration identifies areas of homogeneous land cover at the nominal spatial resolution of the MODIS (MCD43A) albedo product (500&nbsp;m&nbsp;×&nbsp;500&nbsp;m) from the NLCD product (30&nbsp;m&nbsp;×&nbsp;30&nbsp;m), and provides an albedo data record per 500&nbsp;m&nbsp;×&nbsp;500&nbsp;m pixel for 14 of the 16 NLCD land cover classes. Individual homogeneous land cover pixels have up to 605 albedo observations, and 75% of the pixels have at least 319 MODIS albedo observations (≥&nbsp;50% of the maximum possible number of observations) for the study period (2000–2013). We demonstrated the utility of the database by conducting a multivariate analysis of variance of albedo for each NLCD land cover class, showing that locational (pixel-to-pixel) and inter-annual variability were significant factors in addition to expected seasonal (intra-annual) and geographic (latitudinal) effects.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2015.09.012","usgsCitation":"Wickham, J., Barnes, C., Nash, M., and Wade, T., 2015, Combining NLCD and MODIS to create a land cover-albedo database for the continental United States: Remote Sensing of Environment, v. 170, p. 143-152, https://doi.org/10.1016/j.rse.2015.09.012.","productDescription":"10 p.","startPage":"143","endPage":"152","ipdsId":"IP-069951","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":346099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"170","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59cb6734e4b017cf3141c6a7","contributors":{"authors":[{"text":"Wickham, J.","contributorId":102230,"corporation":false,"usgs":true,"family":"Wickham","given":"J.","email":"","affiliations":[],"preferred":false,"id":711200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnes, Christopher A. 0000-0002-4608-4364 christopher.barnes.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-4608-4364","contributorId":178108,"corporation":false,"usgs":true,"family":"Barnes","given":"Christopher A.","email":"christopher.barnes.ctr@usgs.gov","affiliations":[],"preferred":false,"id":711201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nash, M.S.","contributorId":43946,"corporation":false,"usgs":true,"family":"Nash","given":"M.S.","email":"","affiliations":[],"preferred":false,"id":711202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wade, T.G.","contributorId":74113,"corporation":false,"usgs":true,"family":"Wade","given":"T.G.","email":"","affiliations":[],"preferred":false,"id":711203,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70162509,"text":"70162509 - 2015 - Validation of simulated earthquake ground motions based on evolution of intensity and frequency content","interactions":[],"lastModifiedDate":"2016-01-28T09:10:09","indexId":"70162509","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Validation of simulated earthquake ground motions based on evolution of intensity and frequency content","docAbstract":"<p><span>Simulated earthquake ground motions can be used in many recent engineering applications that require time series as input excitations. However, applicability and validation of simulations are subjects of debate in the seismological and engineering communities. We propose a validation methodology at the waveform level and directly based on characteristics that are expected to influence most structural and geotechnical response parameters. In particular, three time-dependent validation metrics are used to evaluate the evolving intensity, frequency, and bandwidth of a waveform. These validation metrics capture nonstationarities in intensity and frequency content of waveforms, making them ideal to address nonlinear response of structural systems. A two-component error vector is proposed to quantify the average and shape differences between these validation metrics for a simulated and recorded ground-motion pair. Because these metrics are directly related to the waveform characteristics, they provide easily interpretable feedback to seismologists for modifying their ground-motion simulation models. To further simplify the use and interpretation of these metrics for engineers, it is shown how six scalar key parameters, including duration, intensity, and predominant frequency, can be extracted from the validation metrics. The proposed validation methodology is a step forward in paving the road for utilization of simulated ground motions in engineering practice and is demonstrated using examples of recorded and simulated ground motions from the 1994 Northridge, California, earthquake.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120140210","usgsCitation":"Rezaeian, S., Zhong, P., Hartzell, S.H., and Zareian, F., 2015, Validation of simulated earthquake ground motions based on evolution of intensity and frequency content: Bulletin of the Seismological Society of America, v. 105, no. 6, p. 3036-3049, https://doi.org/10.1785/0120140210.","productDescription":"14 p.","startPage":"3036","endPage":"3049","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068675","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":314936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles","otherGeospatial":"Northridge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.55552673339842,\n              34.20044475954112\n            ],\n            [\n              -118.55552673339842,\n              34.27651009584797\n            ],\n            [\n              -118.47278594970702,\n              34.27651009584797\n            ],\n            [\n              -118.47278594970702,\n              34.20044475954112\n            ],\n            [\n              -118.55552673339842,\n              34.20044475954112\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"105","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-03","publicationStatus":"PW","scienceBaseUri":"56ab49d8e4b07ca61bfea61a","contributors":{"authors":[{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":589705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhong, Peng","contributorId":152543,"corporation":false,"usgs":false,"family":"Zhong","given":"Peng","email":"","affiliations":[{"id":6641,"text":"University of California at Merced","active":true,"usgs":false}],"preferred":false,"id":589706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":589707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zareian, Farzin","contributorId":152544,"corporation":false,"usgs":false,"family":"Zareian","given":"Farzin","email":"","affiliations":[{"id":6641,"text":"University of California at Merced","active":true,"usgs":false}],"preferred":false,"id":589708,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70160784,"text":"70160784 - 2015 - Large-scale control site selection for population monitoring: an example assessing Sage-grouse trends","interactions":[],"lastModifiedDate":"2015-12-31T13:03:13","indexId":"70160784","displayToPublicDate":"2015-12-01T00:00:00","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":"Large-scale control site selection for population monitoring: an example assessing Sage-grouse trends","docAbstract":"<p>Human impacts on wildlife populations are widespread and prolific and understanding wildlife responses to human impacts is a fundamental component of wildlife management. The first step to understanding wildlife responses is the documentation of changes in wildlife population parameters, such as population size. Meaningful assessment of population changes in potentially impacted sites requires the establishment of monitoring at similar, nonimpacted, control sites. However, it is often difficult to identify appropriate control sites in wildlife populations. We demonstrated use of Geographic Information System (GIS) data across large spatial scales to select biologically relevant control sites for population monitoring. Greater sage-grouse (Centrocercus urophasianus; hearafter, sage-grouse) are negatively affected by energy development, and monitoring of sage-grouse population within energy development areas is necessary to detect population-level responses. Weused population data (1995&ndash;2012) from an energy development area in Wyoming, USA, the Atlantic Rim Project Area (ARPA), and GIS data to identify control sites that were not impacted by energy development for population monitoring. Control sites were surrounded by similar habitat and were within similar climate areas to the ARPA. We developed nonlinear trend models for both the ARPA and control sites and compared long-term trends from the 2 areas. We found little difference between the ARPA and control sites trends over time. This research demonstrated an approach for control site selection across large landscapes and can be used as a template for similar impact-monitoring studies. It is important to note that identification of changes in population parameters between control and treatment sites is only the first step in understanding the mechanisms that underlie those changes. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.</p>","language":"English","publisher":"Wiley","doi":"10.1002/wsb.601","usgsCitation":"Fedy, B.C., O’Donnell, M.S., and Bowen, Z.H., 2015, Large-scale control site selection for population monitoring: an example assessing Sage-grouse trends: Wildlife Society Bulletin, v. 39, no. 4, p. 700-712, https://doi.org/10.1002/wsb.601.","productDescription":"13 p.","startPage":"700","endPage":"712","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053414","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":499960,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/1512b0d458ea4c8ab77bd670ee6a3220","text":"External Repository"},{"id":313148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"South-Central","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.226806640625,\n              42.99259451971113\n            ],\n            [\n              -109.21508789062499,\n              42.97250158602597\n            ],\n            [\n              -109.97863769531249,\n              43.11702412135048\n            ],\n            [\n              -110.841064453125,\n              43.56845179881218\n            ],\n            [\n              -110.841064453125,\n              43.28920196020127\n            ],\n            [\n              -110.9124755859375,\n              42.601619944327965\n            ],\n            [\n              -111.05529785156249,\n              42.589488572714245\n            ],\n            [\n              -111.03881835937499,\n              41.000629848685385\n            ],\n            [\n              -108.2208251953125,\n              41.01721057822846\n            ],\n            [\n              -108.1109619140625,\n              41.27367811566259\n            ],\n            [\n              -107.0562744140625,\n              41.611335399441735\n            ],\n            [\n              -106.3421630859375,\n              41.693424216151314\n            ],\n            [\n              -106.226806640625,\n              42.99259451971113\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"39","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-13","publicationStatus":"PW","scienceBaseUri":"56865fc8e4b0e7594ee74ccf","contributors":{"authors":[{"text":"Fedy, Bradley C.","contributorId":64080,"corporation":false,"usgs":true,"family":"Fedy","given":"Bradley","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":583891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":583890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowen, Zachary H. 0000-0002-8656-1831 bowenz@usgs.gov","orcid":"https://orcid.org/0000-0002-8656-1831","contributorId":821,"corporation":false,"usgs":true,"family":"Bowen","given":"Zachary","email":"bowenz@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":583892,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70177798,"text":"70177798 - 2015 - Evaluation of three aging techniques and back-calculated growth for introduced Blue Catfish from Lake Oconee, Georgia","interactions":[],"lastModifiedDate":"2016-10-21T15:08:42","indexId":"70177798","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of three aging techniques and back-calculated growth for introduced Blue Catfish from Lake Oconee, Georgia","docAbstract":"<p><span>Back-calculation of length-at-age from otoliths and spines is a common technique employed in fisheries biology, but few studies have compared the precision of data collected with this method for catfish populations. We compared precision of back-calculated lengths-at-age for an introduced</span><i>Ictalurus furcatus</i><span> (Blue Catfish) population among 3 commonly used cross-sectioning techniques. We used gillnets to collect Blue Catfish (</span><i>n</i><span> = 153) from Lake Oconee, GA. We estimated ages from a basal recess, articulating process, and otolith cross-section from each fish. We employed the Frasier-Lee method to back-calculate length-at-age for each fish, and compared the precision of back-calculated lengths among techniques using hierarchical linear models. Precision in age assignments was highest for otoliths (83.5%) and lowest for basal recesses (71.4%). Back-calculated lengths were variable among fish ages 1–3 for the techniques compared; otoliths and basal recesses yielded variable lengths at age 8. We concluded that otoliths and articulating processes are adequate for age estimation of Blue Catfish.</span></p>","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/058.014.0417","usgsCitation":"Homer, M.D., Peterson, J., and Jennings, C.A., 2015, Evaluation of three aging techniques and back-calculated growth for introduced Blue Catfish from Lake Oconee, Georgia: Southeastern Naturalist, v. 14, no. 4, p. 740-756, https://doi.org/10.1656/058.014.0417.","productDescription":"17 p.","startPage":"740","endPage":"756","ipdsId":"IP-036204","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":330326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Lake Oconee","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.37867736816406,\n              33.338559712732525\n            ],\n            [\n              -83.37867736816406,\n              33.714630486382156\n            ],\n            [\n              -83.14178466796875,\n              33.714630486382156\n            ],\n            [\n              -83.14178466796875,\n              33.338559712732525\n            ],\n            [\n              -83.37867736816406,\n              33.338559712732525\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"14","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-18","publicationStatus":"PW","scienceBaseUri":"5810c6d6e4b0f497e79733f7","contributors":{"authors":[{"text":"Homer, Michael D. Jr.","contributorId":176188,"corporation":false,"usgs":false,"family":"Homer","given":"Michael","suffix":"Jr.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":651837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":651838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jennings, Cecil A. 0000-0002-6159-6026 jennings@usgs.gov","orcid":"https://orcid.org/0000-0002-6159-6026","contributorId":874,"corporation":false,"usgs":true,"family":"Jennings","given":"Cecil","email":"jennings@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":651821,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70184230,"text":"70184230 - 2015 - 2014 Update of the Pacific Northwest portion of the U.S. National Seismic Hazard Maps","interactions":[],"lastModifiedDate":"2018-07-15T11:27:04","indexId":"70184230","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"2014 Update of the Pacific Northwest portion of the U.S. National Seismic Hazard Maps","docAbstract":"<p><span>Several aspects of the earthquake characterization were changed for the Pacific Northwest portion of the 2014 update of the national seismic hazard maps, reflecting recent scientific findings. New logic trees were developed for the recurrence parameters of M8-9 earthquakes on the Cascadia subduction zone (CSZ) and for the eastern edge of their rupture zones. These logic trees reflect recent findings of additional M8 CSZ earthquakes using offshore deposits of turbidity flows and onshore tsunami deposits and subsidence. These M8 earthquakes each rupture a portion of the CSZ and occur in the time periods between M9 earthquakes that have an average recurrence interval of about 500 years. The maximum magnitude was increased for deep intraslab earthquakes. An areal source zone to account for the possibility of deep earthquakes under western Oregon was expanded. The western portion of the Tacoma fault was added to the hazard maps.</span></p>","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/111314EQS193M","usgsCitation":"Frankel, A.D., Chen, R., Petersen, M.D., Moschetti, M.P., and Sherrod, B.L., 2015, 2014 Update of the Pacific Northwest portion of the U.S. National Seismic Hazard Maps: Earthquake Spectra, v. 31, no. S1, p. S131-S148, https://doi.org/10.1193/111314EQS193M.","productDescription":"18 p.","startPage":"S131","endPage":"S148","ipdsId":"IP-061661","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":336859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Pacific Northwest","volume":"31","issue":"S1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"58be833ce4b014cc3a3a99f5","contributors":{"authors":[{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":680667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Rui","contributorId":78250,"corporation":false,"usgs":true,"family":"Chen","given":"Rui","affiliations":[],"preferred":false,"id":680773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":680776,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70182765,"text":"70182765 - 2015 - Low resistivity and permeability in actively deforming shear zones on the San Andreas Fault at SAFOD","interactions":[],"lastModifiedDate":"2017-02-28T12:59:39","indexId":"70182765","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Low resistivity and permeability in actively deforming shear zones on the San Andreas Fault at SAFOD","docAbstract":"The San Andreas Fault Observatory at Depth (SAFOD) scientific drillhole near Parkfield, California crosses the San Andreas Fault at a depth of 2.7 km.  Downhole measurements and analysis of core retrieved from Phase 3 drilling reveal two narrow, actively deforming zones of smectite-clay gouge within a roughly 200 m-wide fault damage zone of sandstones, siltstones and mudstones.  Here we report electrical resistivity and permeability measurements on core samples from all of these structural units at effective confining pressures up to 120 MPa.  Electrical resistivity (~10 ohm-m) and permeability (10-21 to 10-22 m2) in the actively deforming zones were one to two orders of magnitude lower than the surrounding damage zone material, consistent with broader-scale observations from the downhole resistivity and seismic velocity logs.  The higher porosity of the clay gouge, 2 to 8 times greater than that in the damage zone rocks, along with surface conduction were the principal factors contributing to the observed low resistivities.  The high percentage of fine-grained clay in the deforming zones also greatly reduced permeability to values low enough to create a barrier to fluid flow across the fault.  Together, resistivity and permeability data can be used to assess the hydrogeologic characteristics of the fault, key to understanding fault structure and strength. The low resistivities and strength measurements of the SAFOD core are consistent with observations of low resistivity clays that are often found in the principal slip zones of other active faults making resistivity logs a valuable tool for identifying these zones.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB012214","usgsCitation":"Morrow, C.A., Lockner, D.A., and Hickman, S.H., 2015, Low resistivity and permeability in actively deforming shear zones on the San Andreas Fault at SAFOD: Journal of Geophysical Research, v. 120, no. 12, p. 8240-8258, https://doi.org/10.1002/2015JB012214.","productDescription":"18 p. ","startPage":"8240","endPage":"8258","ipdsId":"IP-063635","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471607,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012214","text":"Publisher Index Page"},{"id":336346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-21","publicationStatus":"PW","scienceBaseUri":"58b69a42e4b01ccd54ff3faa","contributors":{"authors":[{"text":"Morrow, Carolyn A. 0000-0003-3500-6181 cmorrow@usgs.gov","orcid":"https://orcid.org/0000-0003-3500-6181","contributorId":3206,"corporation":false,"usgs":true,"family":"Morrow","given":"Carolyn","email":"cmorrow@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":673673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":673674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hickman, Stephen H. 0000-0003-2075-9615 hickman@usgs.gov","orcid":"https://orcid.org/0000-0003-2075-9615","contributorId":2705,"corporation":false,"usgs":true,"family":"Hickman","given":"Stephen","email":"hickman@usgs.gov","middleInitial":"H.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":673675,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70173962,"text":"70173962 - 2015 - Geospatial resources for the geologic community: The USGS National Map","interactions":[],"lastModifiedDate":"2016-06-21T15:13:12","indexId":"70173962","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2309,"text":"Journal of Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geospatial resources for the geologic community: The USGS National Map","docAbstract":"<p><span>Geospatial data are a key component of investigating, interpreting, and communicating the geological sciences. Locating geospatial data can be time-consuming, which detracts from time spent on a study because these data are not obviously placed in central locations or are served from many disparate databases. The National Map of the US Geological Survey is a publicly available resource for accessing the geospatial base map data needs of the geological community from a central location. The National Map data are available through a viewer and download platform providing access to eight primary data themes, plus the US Topo and scanned historical topographic maps. The eight themes are elevation, orthoimagery, hydrography, geographic names, boundaries, transportation, structures, and land cover, and they are being offered for download as predefined tiles in formats supported by leading geographic information system software. Data tiles are periodically refreshed to capture the most current content and are an efficient method for disseminating and receiving geospatial information. Elevation data, for example, are offered as a download from the National Map as 1&deg; &times; 1&deg; tiles for the 10- and 30- m products and as 15&prime; &times; 15&prime; tiles for the higher-resolution 3-m product. Vector data sets with smaller file sizes are offered at several tile sizes and formats. Partial tiles are not a download option&mdash;any prestaged data that intersect the requesting bounding box will be, in their entirety, part of the download order. While there are many options for accessing geospatial data via the Web, the National Map represents authoritative sources of data that are documented and can be referenced for citation and inclusion in scientific publications. Therefore, National Map products and services should be part of a geologist&rsquo;s first stop for geospatial information and data.</span></p>","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/682008","usgsCitation":"Witt, E.C., 2015, Geospatial resources for the geologic community: The USGS National Map: Journal of Geology, v. 123, no. 3, p. 283-294, https://doi.org/10.1086/682008.","productDescription":"12 p.","startPage":"283","endPage":"294","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063473","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":324152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a653be4b07657d1a11daa","contributors":{"authors":[{"text":"Witt, Emitt C. III 0000-0002-1814-7807 ecwitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7807","contributorId":1612,"corporation":false,"usgs":true,"family":"Witt","given":"Emitt","suffix":"III","email":"ecwitt@usgs.gov","middleInitial":"C.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":639787,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70192724,"text":"70192724 - 2015 - Differences in ecosystem carbon distribution and nutrient cycling linked to forest tree species composition in a mid-successional boreal forest","interactions":[],"lastModifiedDate":"2017-11-08T13:41:24","indexId":"70192724","displayToPublicDate":"2015-12-01T00:00:00","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":"Differences in ecosystem carbon distribution and nutrient cycling linked to forest tree species composition in a mid-successional boreal forest","docAbstract":"<p><span>In the boreal forest of Alaska, increased fire severity associated with climate change is expanding deciduous forest cover in areas previously dominated by black spruce (</span><i class=\"EmphasisTypeItalic \">Picea mariana</i><span>). Needle-leaf conifer and broad-leaf deciduous species are commonly associated with differences in tree growth, carbon (C) and nutrient cycling, and C accumulation in soils. Although this suggests that changes in tree species composition in Alaska could impact C and nutrient pools and fluxes, few studies have measured these linkages. We quantified C, nitrogen, phosphorus, and base cation pools and fluxes in three stands of black spruce and Alaska paper birch (</span><i class=\"EmphasisTypeItalic \">Betula neoalaskana</i><span>) that established following a single fire event in 1958. Paper birch consistently displayed characteristics of more rapid C and nutrient cycling, including greater aboveground net primary productivity, higher live foliage and litter nutrient concentrations, and larger ammonium and nitrate pools in the soil organic layer (SOL). Ecosystem C stocks (aboveground&nbsp;+&nbsp;SOL&nbsp;+&nbsp;0–10&nbsp;cm mineral soil) were similar for the two species; however, in black spruce, 78% of measured C was found in soil pools, primarily in the SOL, whereas aboveground biomass dominated ecosystem C pools in birch forest. Radiocarbon analysis indicated that approximately one-quarter of the black spruce SOL C accumulated prior to the 1958 fire, whereas no pre-fire C was observed in birch soils. Our findings suggest that tree species exert a strong influence over C and nutrient cycling in boreal forest and forest compositional shifts may have long-term implications for ecosystem C and nutrient dynamics.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10021-015-9912-7","usgsCitation":"Melvin, A.M., Mack, M., Johnstone, J.F., McGuire, A.D., Genet, H., and Schuur, E.A., 2015, Differences in ecosystem carbon distribution and nutrient cycling linked to forest tree species composition in a mid-successional boreal forest: Ecosystems, v. 18, no. 8, p. 1472-1488, https://doi.org/10.1007/s10021-015-9912-7.","productDescription":"17 p.","startPage":"1472","endPage":"1488","ipdsId":"IP-063589","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-08","publicationStatus":"PW","scienceBaseUri":"5a0425c2e4b0dc0b45b453fd","contributors":{"authors":[{"text":"Melvin, April M.","contributorId":200151,"corporation":false,"usgs":false,"family":"Melvin","given":"April","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721276,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mack, Michelle C.","contributorId":140367,"corporation":false,"usgs":false,"family":"Mack","given":"Michelle C.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":721277,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnstone, Jill F.","contributorId":179336,"corporation":false,"usgs":false,"family":"Johnstone","given":"Jill","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":721278,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716777,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Genet, Helene","contributorId":95370,"corporation":false,"usgs":true,"family":"Genet","given":"Helene","affiliations":[],"preferred":false,"id":721279,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schuur, Edward A.G.","contributorId":50026,"corporation":false,"usgs":true,"family":"Schuur","given":"Edward","email":"","middleInitial":"A.G.","affiliations":[],"preferred":false,"id":721280,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70175500,"text":"70175500 - 2015 - Long Valley caldera and the UCERF depiction of Sierra Nevada range-front faults","interactions":[],"lastModifiedDate":"2016-08-15T16:00:14","indexId":"70175500","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Long Valley caldera and the UCERF depiction of Sierra Nevada range-front faults","docAbstract":"<p><span>Long Valley caldera lies within a left-stepping offset in the north-northwest-striking Sierra Nevada range-front normal faults with the Hilton Creek fault to the south and Hartley Springs fault to the north. Both Uniform California Earthquake Rupture Forecast (UCERF) 2 and its update, UCERF3, depict slip on these major range-front normal faults as extending well into the caldera, with significant normal slip on overlapping, subparallel segments separated by &sim;10&thinsp;&thinsp;km. This depiction is countered by (1)&nbsp;geologic evidence that normal faulting within the caldera consists of a series of graben structures associated with postcaldera magmatism (intrusion and tumescence) and not systematic down-to-the-east displacements consistent with distributed range-front faulting and (2)&nbsp;the lack of kinematic evidence for an evolving, postcaldera relay ramp structure between overlapping strands of the two range-front normal faults. The modifications to the UCERF depiction described here reduce the predicted shaking intensity within the caldera, and they are in accord with the tectonic influence that underlapped offset range-front faults have on seismicity patterns within the caldera associated with ongoing volcanic unrest.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120150149","usgsCitation":"Hill, D.P., and Montgomery-Brown, E.K., 2015, Long Valley caldera and the UCERF depiction of Sierra Nevada range-front faults: Bulletin of the Seismological Society of America, v. 105, no. 6, p. 3189-3195, https://doi.org/10.1785/0120150149.","productDescription":"7 p.","startPage":"3189","endPage":"3195","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066077","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":326504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-10","publicationStatus":"PW","scienceBaseUri":"57b2e7bfe4b03bcb0102e90e","contributors":{"authors":[{"text":"Hill, David P. hill@usgs.gov","contributorId":2600,"corporation":false,"usgs":true,"family":"Hill","given":"David","email":"hill@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":645508,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Montgomery-Brown, Emily K. emontgomery-brown@usgs.gov","contributorId":5300,"corporation":false,"usgs":true,"family":"Montgomery-Brown","given":"Emily","email":"emontgomery-brown@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":false,"id":645509,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70176400,"text":"70176400 - 2015 - Quantifying the residence time and flushing characteristics of a shallow, back-barrier estuary: Application of hydrodynamic and particle tracking models","interactions":[],"lastModifiedDate":"2016-09-13T09:39:55","indexId":"70176400","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the residence time and flushing characteristics of a shallow, back-barrier estuary: Application of hydrodynamic and particle tracking models","docAbstract":"<p><span>Estuarine residence time is a major driver of eutrophication and water quality. Barnegat Bay-Little Egg Harbor (BB-LEH), New Jersey, is a lagoonal back-barrier estuary that is subject to anthropogenic pressures including nutrient loading, eutrophication, and subsequent declines in water quality. A combination of hydrodynamic and particle tracking modeling was used to identify the mechanisms controlling flushing, residence time, and spatial variability of particle retention. The models demonstrated a pronounced northward subtidal flow from Little Egg Inlet in the south to Pt. Pleasant Canal in the north due to frictional effects in the inlets, leading to better flushing of the southern half of the estuary and particle retention in the northern estuary. Mean residence time for BB-LEH was 13&nbsp;days but spatial variability was between ∼0 and 30&nbsp;days depending on the initial particle location. Mean residence time with tidal forcing alone was 24&nbsp;days (spatial variability between ∼0 and 50&nbsp;days); the tides were relatively inefficient in flushing the northern end of the Bay. Scenarios with successive exclusion of physical processes from the models revealed that meteorological and remote offshore forcing were stronger drivers of exchange than riverine inflow. Investigations of water quality and eutrophication should take into account spatial variability in hydrodynamics and residence time in order to better quantify the roles of nutrient loading, production, and flushing.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s12237-014-9885-3","usgsCitation":"Defne, Z., and Ganju, N., 2015, Quantifying the residence time and flushing characteristics of a shallow, back-barrier estuary: Application of hydrodynamic and particle tracking models: Estuaries and Coasts, v. 38, no. 5, p. 1719-1734, https://doi.org/10.1007/s12237-014-9885-3.","productDescription":"16 p.","startPage":"1719","endPage":"1734","ipdsId":"IP-057196","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471614,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/7506","text":"External Repository"},{"id":328587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"5","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-23","publicationStatus":"PW","scienceBaseUri":"57d92340e4b090824ffa1b23","contributors":{"authors":[{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":149613,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","email":"nganju@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":648604,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70178476,"text":"70178476 - 2015 - SPARROW modeling of nitrogen sources and transport in rivers and streams of California and adjacent states, U.S.","interactions":[],"lastModifiedDate":"2016-11-21T13:09:04","indexId":"70178476","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"SPARROW modeling of nitrogen sources and transport in rivers and streams of California and adjacent states, U.S.","docAbstract":"<p><span>The SPARROW (SPAtially Referenced Regressions On Watershed attributes) model was used to evaluate the spatial distribution of total nitrogen (TN) sources, loads, watershed yields, and factors affecting transport and decay in the stream network of California and portions of adjacent states for the year 2002. The two major TN sources to local catchments on a mass basis were fertilizers and manure (51.7%) and wastewater discharge (15.9%). Other sources contributed &lt;&nbsp;12%. Fertilizer use is widespread in the Central Valley region of California, and also important in several other regions because of the diversity of California agriculture. Precipitation, sand content of surficial soils, wetlands, and tile drains were important for TN movement to stream reaches. Median streamflow in the study area is about 0.04&nbsp;m</span><sup>3</sup><span>/s. Aquatic losses of nitrogen were found to be most important in intermittent and small to medium sized streams (0.2-14&nbsp;m</span><sup>3</sup><span>/s), while larger streams showed less loss, and therefore are important for TN transport. Nitrogen loss in reservoirs was found to be insignificant, possibly because most of the larger ones are located upstream of nitrogen sources. The model was used to show loadings, sources, and tributary inputs to several major rivers. The information provided by the SPARROW model is useful for determining both the major sources contributing nitrogen to streams and the specific tributaries that transport the load.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12325","usgsCitation":"Saleh, D., and Domagalski, J.L., 2015, SPARROW modeling of nitrogen sources and transport in rivers and streams of California and adjacent states, U.S.: Journal of the American Water Resources Association, v. 51, no. 6, p. 1487-1507, https://doi.org/10.1111/1752-1688.12325.","productDescription":"20 p.","startPage":"1487","endPage":"1507","ipdsId":"IP-044910","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":331159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70169234,"text":"70169234 - 2015 - Assessment of model estimates of land-atmosphere CO<sub>2</sub> exchange across northern Eurasia","interactions":[],"lastModifiedDate":"2016-03-24T13:40:28","indexId":"70169234","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of model estimates of land-atmosphere CO<sub>2</sub> exchange across northern Eurasia","docAbstract":"<p><span>A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO</span><span>2</span><span>) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960&ndash;2009 at 0.5&deg; resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO</span><span>2</span><span>&nbsp;fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m</span><span>&minus;2</span><span>&nbsp;yr</span><span>&minus;2</span><span>, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960&ndash;1969 vs. 2000&ndash;2009), with a weakening CO</span><span>2</span><span>&nbsp;sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO</span><span>2</span><span>&nbsp;sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO</span><span>2</span><span>&nbsp;exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-12-4385-2015","usgsCitation":"Rawlins, M., McGuire, A., Kimball, J., Dass, P., Lawrence, D., Burke, E., Chen, X., Delire, C., Koven, C., MacDougall, A., Peng, S., Rinke, A., Saito, K., Zhang, W., Alkama, R., Bohn, T.J., Ciais, P., Decharme, B., Gouttevin, I., Hajima, T., Ji, D., Krinner, G., Lettenmaier, D., Miller, P., Moore, J., Smith, B., and Sueyoshi, T., 2015, Assessment of model estimates of land-atmosphere CO<sub>2</sub> exchange across northern Eurasia: Biogeosciences, v. 12, no. 14, p. 4385-4405, https://doi.org/10.5194/bg-12-4385-2015.","productDescription":"21 p.","startPage":"4385","endPage":"4405","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059953","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471618,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-12-4385-2015","text":"Publisher Index Page"},{"id":319370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Eurasia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.68242645263672,\n              46.13036330589103\n            ],\n            [\n              -89.68242645263672,\n              46.150107913663334\n            ],\n            [\n              -89.65873718261719,\n              46.150107913663334\n            ],\n            [\n              -89.65873718261719,\n              46.13036330589103\n            ],\n            [\n              -89.68242645263672,\n              46.13036330589103\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.73096370697021,\n              45.77300107536654\n            ],\n            [\n              -89.73096370697021,\n              45.78153149170592\n            ],\n            [\n              -89.71843242645264,\n              45.78153149170592\n            ],\n            [\n              -89.71843242645264,\n              45.77300107536654\n            ],\n            [\n              -89.73096370697021,\n              45.77300107536654\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              5.9765625,\n              51.39920565355378\n            ],\n            [\n              5.9765625,\n              77.38950400539731\n            ],\n            [\n              180.35156249999997,\n              77.38950400539731\n            ],\n            [\n              180.35156249999997,\n              51.39920565355378\n            ],\n            [\n              5.9765625,\n              51.39920565355378\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"14","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-28","publicationStatus":"PW","scienceBaseUri":"56f50fb0e4b0f59b85e1ea97","contributors":{"authors":[{"text":"Rawlins, M.A.","contributorId":73445,"corporation":false,"usgs":true,"family":"Rawlins","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":623730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, A. 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