{"pageNumber":"719","pageRowStart":"17950","pageSize":"25","recordCount":40783,"records":[{"id":70032630,"text":"70032630 - 2012 - Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests","interactions":[],"lastModifiedDate":"2013-06-20T10:22:30","indexId":"70032630","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests","docAbstract":"The timing of spring leaf development, trajectories of summer leaf area, and the timing of autumn senescence have profound impacts to the water, carbon, and energy balance of ecosystems, and are likely influenced by global climate change. Limited field-based and remote-sensing observations have suggested complex spatial patterns related to geographic features that influence climate. However, much of this variability occurs at spatial scales that inhibit a detailed understanding of even the dominant drivers. Recognizing these limitations, we used nonlinear inverse modeling of medium-resolution remote sensing data, organized by day of year, to explore the influence of climate-related landscape factors on the timing of spring and autumn leaf-area trajectories in mid-Atlantic, USA forests. We also examined the extent to which declining summer greenness (greendown) degrades the precision and accuracy of observations of autumn offset of greenness. Of the dominant drivers of landscape phenology, elevation was the strongest, explaining up to 70% of the spatial variation in the onset of greenness. Urban land cover was second in importance, influencing spring onset and autumn offset to a distance of 32 km from large cities. Distance to tidal water also influenced phenological timing, but only within ~5 km of shorelines. Additionally, we observed that (i) growing season length unexpectedly increases with increasing elevation at elevations below 275 m; (ii) along gradients in urban land cover, timing of autumn offset has a stronger effect on growing season length than does timing of spring onset; and (iii) summer greendown introduces bias and uncertainty into observations of the autumn offset of greenness. These results demonstrate the power of medium grain analyses of landscape-scale phenology for understanding environmental controls on growing season length, and predicting how these might be affected by climate change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Global Change Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1365-2486.2011.02521.x","issn":"13541013","usgsCitation":"Elmore, A., Guinn, S., Minsley, B., and Richardson, A., 2012, Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests: Global Change Biology, v. 18, no. 2, p. 656-674, https://doi.org/10.1111/j.1365-2486.2011.02521.x.","productDescription":"19 p.","startPage":"656","endPage":"674","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":241560,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213892,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2486.2011.02521.x"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-09-19","publicationStatus":"PW","scienceBaseUri":"505a4408e4b0c8380cd667c5","contributors":{"authors":[{"text":"Elmore, A.J.","contributorId":103095,"corporation":false,"usgs":true,"family":"Elmore","given":"A.J.","email":"","affiliations":[],"preferred":false,"id":437138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guinn, S.M.","contributorId":35552,"corporation":false,"usgs":true,"family":"Guinn","given":"S.M.","email":"","affiliations":[],"preferred":false,"id":437136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minsley, B. J.","contributorId":52107,"corporation":false,"usgs":true,"family":"Minsley","given":"B. J.","affiliations":[],"preferred":false,"id":437137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richardson, A.D.","contributorId":10629,"corporation":false,"usgs":true,"family":"Richardson","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":437135,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70035492,"text":"70035492 - 2012 - An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system","interactions":[],"lastModifiedDate":"2020-11-23T16:39:21.889556","indexId":"70035492","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system","docAbstract":"<p><span>Accurate topographic data are critical to restoration science and planning for the Everglades region of South Florida, USA. They are needed to monitor and simulate water level, water depth and hydroperiod and are used in scientific research on hydrologic and biologic processes. Because large wetland environments and data acquisition challenge conventional ground-based and remotely sensed data collection methods, the United States Geological Survey (USGS) adapted a classical data collection instrument to global positioning system (GPS) and geographic information system (GIS) technologies. Data acquired with this instrument were processed using geostatistics to yield sub-water level elevation values with centimetre accuracy (±15 cm). The developed database framework, modelling philosophy and metadata protocol allow for continued, collaborative model revision and expansion, given additional elevation or other ancillary data.</span></p>","language":"English","publisher":"Taylor & Francis Online","doi":"10.1080/01431161.2010.533212","issn":"01431161","usgsCitation":"Jones, J.W., Desmond, G., Henkle, C., and Glover, R., 2012, An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system: International Journal of Remote Sensing, v. 33, no. 2, p. 450-465, https://doi.org/10.1080/01431161.2010.533212.","productDescription":"16 p.","startPage":"450","endPage":"465","costCenters":[],"links":[{"id":242952,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215170,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2010.533212"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.14501953125,\n              25.105497373014686\n            ],\n            [\n              -80.22216796875,\n              25.145284610685064\n            ],\n            [\n              -79.8486328125,\n              25.898761936567023\n            ],\n            [\n              -79.9365234375,\n              26.33280692289788\n            ],\n            [\n              -82.0458984375,\n              26.33280692289788\n            ],\n            [\n              -81.14501953125,\n              25.105497373014686\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"33","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-10-28","publicationStatus":"PW","scienceBaseUri":"5059ea0ce4b0c8380cd485db","contributors":{"authors":[{"text":"Jones, J. W.","contributorId":89233,"corporation":false,"usgs":true,"family":"Jones","given":"J.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":450891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Desmond, G.B.","contributorId":35014,"corporation":false,"usgs":true,"family":"Desmond","given":"G.B.","email":"","affiliations":[],"preferred":false,"id":450890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henkle, C.","contributorId":91319,"corporation":false,"usgs":true,"family":"Henkle","given":"C.","email":"","affiliations":[],"preferred":false,"id":450892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glover, R.","contributorId":103106,"corporation":false,"usgs":true,"family":"Glover","given":"R.","email":"","affiliations":[],"preferred":false,"id":450893,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70035490,"text":"70035490 - 2012 - Modifications to the conduit flow process mode 2 for MODFLOW-2005","interactions":[],"lastModifiedDate":"2020-11-24T12:35:59.930906","indexId":"70035490","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Modifications to the conduit flow process mode 2 for MODFLOW-2005","docAbstract":"<p><span>As a result of rock dissolution processes, karst aquifers exhibit highly conductive features such as caves and conduits. Within these structures, groundwater flow can become turbulent and therefore be described by nonlinear gradient functions. Some numerical groundwater flow models explicitly account for pipe hydraulics by coupling the continuum model with a pipe network that represents the conduit system. In contrast, the Conduit Flow Process Mode 2 (CFPM2) for MODFLOW‐2005 approximates turbulent flow by reducing the hydraulic conductivity within the existing linear head gradient of the MODFLOW continuum model. This approach reduces the practical as well as numerical efforts for simulating turbulence. The original formulation was for large pore aquifers where the onset of turbulence is at low Reynolds numbers (1 to 100) and not for conduits or pipes. In addition, the existing code requires multiple time steps for convergence due to iterative adjustment of the hydraulic conductivity. Modifications to the existing CFPM2 were made by implementing a generalized power function with a user‐defined exponent. This allows for matching turbulence in porous media or pipes and eliminates the time steps required for iterative adjustment of hydraulic conductivity. The modified CFPM2 successfully replicated simple benchmark test problems.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1745-6584.2011.00805.x","issn":"0017467X","usgsCitation":"Reimann, T., Birk, S., Rehrl, C., and Shoemaker, W., 2012, Modifications to the conduit flow process mode 2 for MODFLOW-2005: Ground Water, v. 50, no. 1, p. 144-148, https://doi.org/10.1111/j.1745-6584.2011.00805.x.","productDescription":"5 p.","startPage":"144","endPage":"148","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":242950,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-03-03","publicationStatus":"PW","scienceBaseUri":"505a5cbbe4b0c8380cd6fee4","contributors":{"authors":[{"text":"Reimann, Thomas","contributorId":45536,"corporation":false,"usgs":true,"family":"Reimann","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":450885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birk, S.","contributorId":41182,"corporation":false,"usgs":true,"family":"Birk","given":"S.","email":"","affiliations":[],"preferred":false,"id":450884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rehrl, C.","contributorId":33938,"corporation":false,"usgs":true,"family":"Rehrl","given":"C.","email":"","affiliations":[],"preferred":false,"id":450883,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shoemaker, W. Barclay","contributorId":215321,"corporation":false,"usgs":true,"family":"Shoemaker","given":"W. Barclay","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":450886,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70035459,"text":"70035459 - 2012 - Fate and transport of glyphosate and aminomethylphosphonic acid in surface waters of agricultural basins","interactions":[],"lastModifiedDate":"2020-11-23T17:23:00.33329","indexId":"70035459","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3035,"text":"Pest Management Science","active":true,"publicationSubtype":{"id":10}},"title":"Fate and transport of glyphosate and aminomethylphosphonic acid in surface waters of agricultural basins","docAbstract":"<p>BACKGROUND: Glyphosate [N-(phosphonomethyl)glycine] is a herbicide used widely throughout the world in the production of many crops and is heavily used on soybeans, corn and cotton. Glyphosate is used in almost all agricultural areas of the United States, and the agricultural use of glyphosate has increased from less than 10 000 Mg in 1992 to more than 80 000 Mg in 2007. The greatest intensity of glyphosate use is in the midwestern United States, where applications are predominantly to genetically modified corn and soybeans. In spite of the increase in usage across the United States, the characterization of the transport of glyphosate and its degradate aminomethylphosphonic acid (AMPA) on a watershed scale is lacking. </p><p>RESULTS: Glyphosate and AMPA were frequently detected in the surface waters of four agricultural basins. The frequency and magnitude of detections varied across basins, and the load, as a percentage of use, ranged from 0.009 to 0.86% and could be related to three general characteristics: source strength, rainfall runoff and flow route. </p><p>CONCLUSIONS: Glyphosate use in a watershed results in some occurrence in surface water; however, the watersheds most at risk for the offsite transport of glyphosate are those with high application rates, rainfall that results in overland runoff and a flow route that does not include transport through the soil.</p>","language":"English","publisher":"Wiley","doi":"10.1002/ps.2212","issn":"1526498X","usgsCitation":"Coupe, R.H., Kalkhoff, S.J., Capel, P.D., and Gregoire, C., 2012, Fate and transport of glyphosate and aminomethylphosphonic acid in surface waters of agricultural basins: Pest Management Science, v. 68, no. 1, p. 16-30, https://doi.org/10.1002/ps.2212.","productDescription":"15 p.","startPage":"16","endPage":"30","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":242878,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215104,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ps.2212"}],"volume":"68","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-06-16","publicationStatus":"PW","scienceBaseUri":"505a0f09e4b0c8380cd53722","contributors":{"authors":[{"text":"Coupe, Richard H. 0000-0001-8679-1015 rhcoupe@usgs.gov","orcid":"https://orcid.org/0000-0001-8679-1015","contributorId":551,"corporation":false,"usgs":true,"family":"Coupe","given":"Richard","email":"rhcoupe@usgs.gov","middleInitial":"H.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"preferred":true,"id":450771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalkhoff, Stephen J. 0000-0003-4110-1716 sjkalkho@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-1716","contributorId":1731,"corporation":false,"usgs":true,"family":"Kalkhoff","given":"Stephen","email":"sjkalkho@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":450769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":450772,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gregoire, Caroline","contributorId":7576,"corporation":false,"usgs":true,"family":"Gregoire","given":"Caroline","email":"","affiliations":[],"preferred":false,"id":450770,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70032658,"text":"70032658 - 2012 - Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA","interactions":[],"lastModifiedDate":"2017-11-21T15:18:55","indexId":"70032658","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA","docAbstract":"<p><span>Nitrate leaching in the unsaturated zone poses a risk to groundwater, whereas nitrate in tile drainage is conveyed directly to streams. We developed metamodels (MMs) consisting of artificial neural networks to simplify and upscale mechanistic fate and transport models for prediction of nitrate losses by drains and leaching in the Corn Belt, USA. The two final MMs predicted nitrate concentration and flux, respectively, in the shallow subsurface. Because each MM considered both tile drainage and leaching, they represent an integrated approach to vulnerability assessment. The MMs used readily available data comprising farm fertilizer nitrogen (N), weather data, and soil properties as inputs; therefore, they were well suited for regional extrapolation. The MMs effectively related the outputs of the underlying mechanistic model (Root Zone Water Quality Model) to the inputs (R</span><sup>2</sup><span><span>&nbsp;</span>= 0.986 for the nitrate concentration MM). Predicted nitrate concentration was compared with measured nitrate in 38 samples of recently recharged groundwater, yielding a Pearson’s<span>&nbsp;</span></span><i>r</i><span><span>&nbsp;</span>of 0.466 (</span><i>p</i><span><span>&nbsp;</span>= 0.003). Predicted nitrate generally was higher than that measured in groundwater, possibly as a result of the time-lag for modern recharge to reach well screens, denitrification in groundwater, or interception of recharge by tile drains. In a qualitative comparison, predicted nitrate concentration also compared favorably with results from a previous regression model that predicted total N in streams.</span></p>","language":"English","publisher":"ACS","doi":"10.1021/es202875e","issn":"0013936X","usgsCitation":"Nolan, B.T., Malone, R.W., Gronberg, J., Thorp, K., and Ma, L., 2012, Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA: Environmental Science & Technology, v. 46, no. 2, p. 901-908, https://doi.org/10.1021/es202875e.","productDescription":"8 p.","startPage":"901","endPage":"908","numberOfPages":"8","ipdsId":"IP-031037","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":241524,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213859,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es202875e"}],"volume":"46","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-12-22","publicationStatus":"PW","scienceBaseUri":"505bc218e4b08c986b32a905","contributors":{"authors":[{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":437321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malone, Robert W.","contributorId":10347,"corporation":false,"usgs":false,"family":"Malone","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":437325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gronberg, Jo Ann M.","contributorId":18342,"corporation":false,"usgs":true,"family":"Gronberg","given":"Jo Ann M.","affiliations":[],"preferred":false,"id":437324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorp, K.R.","contributorId":38370,"corporation":false,"usgs":true,"family":"Thorp","given":"K.R.","email":"","affiliations":[],"preferred":false,"id":437323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ma, Liwang","contributorId":29140,"corporation":false,"usgs":true,"family":"Ma","given":"Liwang","email":"","affiliations":[],"preferred":false,"id":437322,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70035366,"text":"70035366 - 2012 - Monitoring on Xi'an ground fissures deformation with TerraSAR-X data","interactions":[],"lastModifiedDate":"2012-03-12T17:21:56","indexId":"70035366","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3798,"text":"Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring on Xi'an ground fissures deformation with TerraSAR-X data","docAbstract":"Owing to the fine resolution of TerraSAR-X data provided since 2007, this paper applied 6 TerraSAR data (strip mode) during 3rd Dec. 2009 to 23rd Mar. 2010 to detect and monitor the active fissures over Xi'an region. Three themes have been designed for high precision detection and monitoring of Xi'an-Chang'an fissures, as small baseline subsets (SBAS) to test the atmospheric effects of differential interferograms pair stepwise, 2-pass differential interferogram with very short baseline perpendicular to generate the whole deformation map with 44 days interval, and finally, corner reflector (CR) technique was used to closely monitor the relative deformation time series between two CRs settled crossing two ground fissures. Results showed that TerraSAR data are a good choice for small-scale ground fissures detection and monitoring, while special considerations should be taken for their great temporal and baseline decorrelation. Secondly, ground fissures in Xi'an were mostly detected at the joint section of stable and deformable regions. Lastly, CR-InSAR had potential ability to monitor relative deformation crossing fissures with millimeter precision.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"Chinese","issn":"16718860","usgsCitation":"Zhao, C., Zhang, Q., Zhu, W., and Lu, Z., 2012, Monitoring on Xi'an ground fissures deformation with TerraSAR-X data: Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, v. 37, no. 1, p. 81-85.","startPage":"81","endPage":"85","numberOfPages":"5","costCenters":[],"links":[{"id":243011,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5dd0e4b0c8380cd705f0","contributors":{"authors":[{"text":"Zhao, C.","contributorId":14655,"corporation":false,"usgs":true,"family":"Zhao","given":"C.","email":"","affiliations":[],"preferred":false,"id":450351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Q.","contributorId":84163,"corporation":false,"usgs":true,"family":"Zhang","given":"Q.","email":"","affiliations":[],"preferred":false,"id":450353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, W.","contributorId":27686,"corporation":false,"usgs":true,"family":"Zhu","given":"W.","email":"","affiliations":[],"preferred":false,"id":450352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Z.","contributorId":106241,"corporation":false,"usgs":true,"family":"Lu","given":"Z.","affiliations":[],"preferred":false,"id":450354,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70032667,"text":"70032667 - 2012 - An experimental test and models of drift and dispersal processes of pallid sturgeon (Scaphirhynchus albus) free embryos in the Missouri River","interactions":[],"lastModifiedDate":"2016-10-13T11:08:06","indexId":"70032667","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"An experimental test and models of drift and dispersal processes of pallid sturgeon (Scaphirhynchus albus) free embryos in the Missouri River","docAbstract":"Free embryos of wild pallid sturgeon Scaphirhynchus albus were released in the Missouri River and captured at downstream sites through a 180-km reach of the river to examine ontogenetic drift and dispersal processes. Free embryos drifted primarily in the fastest portion of the river channel, and initial drift velocities for all age groups (mean = 0.66–0.70 m s<sup>−1</sup>) were only slightly slower than mean water column velocity (0.72 m s<sup>−1</sup>). During the multi-day long-distance drift period, drift velocities of all age groups declined an average of 9.7% day<sup>−1</sup>. Younger free embryos remained in the drift upon termination of the study; whereas, older age groups transitioned from drifting to settling during the study. Models based on growth of free embryos, drift behavior, size-related variations in drift rates, and channel hydraulic characteristics were developed to estimate cumulative distance drifted during ontogenetic development through a range of simulated water temperatures and velocity conditions. Those models indicated that the average free embryo would be expected to drift several hundred km during ontogenetic development. Empirical data and model results highlight the long-duration, long-distance drift and dispersal processes for pallid sturgeon early life stages. In addition, results provide a likely mechanism for lack of pallid sturgeon recruitment in fragmented river reaches where dams and reservoirs reduce the length of free-flowing river available for pallid sturgeon free embryos during ontogenetic development.","language":"English","publisher":"Springer","doi":"10.1007/s10641-011-9925-9","issn":"03781909","usgsCitation":"Braaten, P., Fuller, D., Lott, R., Ruggles, M., Brandt, T., Legare, R., and Holm, R., 2012, An experimental test and models of drift and dispersal processes of pallid sturgeon (Scaphirhynchus albus) free embryos in the Missouri River: Environmental Biology of Fishes, v. 93, no. 3, p. 377-392, https://doi.org/10.1007/s10641-011-9925-9.","productDescription":"16 p.","startPage":"377","endPage":"392","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":241629,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213952,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10641-011-9925-9"}],"volume":"93","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-09-30","publicationStatus":"PW","scienceBaseUri":"5059ea67e4b0c8380cd4883a","contributors":{"authors":[{"text":"Braaten, P.J.","contributorId":98857,"corporation":false,"usgs":true,"family":"Braaten","given":"P.J.","affiliations":[],"preferred":false,"id":437366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, D.B.","contributorId":74116,"corporation":false,"usgs":false,"family":"Fuller","given":"D.B.","email":"","affiliations":[{"id":5099,"text":"Montana Department of Fish, Wildlife, and Parks","active":true,"usgs":false}],"preferred":false,"id":437364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lott, R.D.","contributorId":93172,"corporation":false,"usgs":true,"family":"Lott","given":"R.D.","email":"","affiliations":[],"preferred":false,"id":437365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruggles, M.P.","contributorId":35964,"corporation":false,"usgs":true,"family":"Ruggles","given":"M.P.","email":"","affiliations":[],"preferred":false,"id":437361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brandt, T.F.","contributorId":72912,"corporation":false,"usgs":true,"family":"Brandt","given":"T.F.","email":"","affiliations":[],"preferred":false,"id":437362,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Legare, R.G.","contributorId":15323,"corporation":false,"usgs":true,"family":"Legare","given":"R.G.","email":"","affiliations":[],"preferred":false,"id":437360,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Holm, R.J.","contributorId":73831,"corporation":false,"usgs":true,"family":"Holm","given":"R.J.","email":"","affiliations":[],"preferred":false,"id":437363,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70032723,"text":"70032723 - 2012 - On valuing patches: Estimating contributions to metapopulation growth with reverse-time capture-recapture modelling","interactions":[],"lastModifiedDate":"2020-11-24T12:47:05.824503","indexId":"70032723","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"On valuing patches: Estimating contributions to metapopulation growth with reverse-time capture-recapture modelling","docAbstract":"<p><span>Metapopulation ecology has historically been rich in theory, yet analytical approaches for inferring demographic relationships among local populations have been few. We show how reverse-time multi-state capture–recapture models can be used to estimate the importance of local recruitment and interpopulation dispersal to metapopulation growth. We use ‘contribution metrics’ to infer demographic connectedness among eight local populations of banner-tailed kangaroo rats, to assess their demographic closure, and to investigate sources of variation in these contributions. Using a 7 year dataset, we show that: (i) local populations are relatively independent demographically, and contributions to local population growth via dispersal within the system decline with distance; (ii) growth contributions via local survival and recruitment are greater for adults than juveniles, while contributions involving dispersal are greater for juveniles; (iii) central populations rely more on local recruitment and survival than peripheral populations; (iv) contributions involving dispersal are not clearly related to overall metapopulation density; and (v) estimated contributions from outside the system are unexpectedly large. Our analytical framework can classify metapopulations on a continuum between demographic independence and panmixia, detect hidden population growth contributions, and make inference about other population linkage forms, including rescue effects and source–sink structures. Finally, we discuss differences between demographic and genetic population linkage patterns for our system.</span></p>","language":"English","publisher":"Royal Publishing Society","doi":"10.1098/rspb.2011.0885","issn":"09628452","usgsCitation":"Sanderlin, J., Waser, P., Hines, J., and Nichols, J., 2012, On valuing patches: Estimating contributions to metapopulation growth with reverse-time capture-recapture modelling: Proceedings of the Royal Society B: Biological Sciences, v. 279, no. 1728, p. 480-488, https://doi.org/10.1098/rspb.2011.0885.","productDescription":"9 p.","startPage":"480","endPage":"488","costCenters":[],"links":[{"id":474651,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2011.0885","text":"Publisher Index Page"},{"id":241459,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213800,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1098/rspb.2011.0885"}],"country":"United States","state":"Arizona","county":"Cochise County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-109.0478,32.4251],[-109.0478,32.4059],[-109.0478,32.4016],[-109.0479,32.3866],[-109.0479,32.3576],[-109.048,32.3257],[-109.048,32.3111],[-109.0481,32.266],[-109.0481,32.2514],[-109.0486,32.0745],[-109.0486,32.0391],[-109.0486,31.9747],[-109.0487,31.9592],[-109.0487,31.9408],[-109.0488,31.9112],[-109.0495,31.6101],[-109.0496,31.5944],[-109.0498,31.5717],[-109.0494,31.506],[-109.0497,31.4862],[-109.0498,31.4497],[-109.0499,31.436],[-109.0501,31.3809],[-109.0501,31.3699],[-109.05,31.3319],[-109.2268,31.3323],[-109.2788,31.3322],[-109.3678,31.3321],[-109.3844,31.332],[-109.4021,31.332],[-109.4182,31.3324],[-109.4857,31.3321],[-109.7532,31.3324],[-109.7585,31.3324],[-109.7904,31.3323],[-109.9462,31.3324],[-110.0011,31.3323],[-110.1457,31.3321],[-110.3642,31.3319],[-110.4413,31.3318],[-110.4603,31.3318],[-110.4611,31.3328],[-110.4561,31.3328],[-110.4562,31.4684],[-110.4555,31.5871],[-110.4558,31.6017],[-110.4561,31.6154],[-110.448,31.6157],[-110.4483,31.6536],[-110.4482,31.6883],[-110.4485,31.702],[-110.4485,31.7307],[-110.4482,31.7462],[-110.4484,31.7622],[-110.4481,31.7759],[-110.4467,31.9054],[-110.447,31.9209],[-110.4477,31.993],[-110.4482,32.0518],[-110.4484,32.0668],[-110.4482,32.0801],[-110.446,32.0805],[-110.4444,32.1657],[-110.4443,32.1712],[-110.4437,32.2551],[-110.447,32.2551],[-110.4472,32.2701],[-110.448,32.4274],[-110.3448,32.4268],[-110.3453,32.4255],[-110.2981,32.4252],[-110.2888,32.4255],[-110.2785,32.4254],[-110.2731,32.4258],[-110.2638,32.4256],[-110.2584,32.426],[-110.2296,32.426],[-110.2117,32.4257],[-110.1617,32.4258],[-110.1112,32.4259],[-110.0422,32.4266],[-109.9396,32.4252],[-109.8375,32.4256],[-109.7353,32.4258],[-109.6327,32.4242],[-109.5311,32.4243],[-109.5116,32.4244],[-109.4947,32.4244],[-109.461,32.4241],[-109.4442,32.4242],[-109.4274,32.4248],[-109.3258,32.4238],[-109.3084,32.4234],[-109.2916,32.4234],[-109.2579,32.423],[-109.2405,32.4226],[-109.2242,32.4227],[-109.2242,32.4245],[-109.2068,32.425],[-109.1894,32.4246],[-109.1726,32.4246],[-109.1552,32.4251],[-109.1394,32.4251],[-109.122,32.4252],[-109.1131,32.4251],[-109.0786,32.4249],[-109.0478,32.4251]]]},\"properties\":{\"name\":\"Cochise\",\"state\":\"AZ\"}}]}","volume":"279","issue":"1728","noUsgsAuthors":false,"publicationDate":"2011-06-22","publicationStatus":"PW","scienceBaseUri":"505a6e17e4b0c8380cd754ad","contributors":{"authors":[{"text":"Sanderlin, J.S.","contributorId":98122,"corporation":false,"usgs":true,"family":"Sanderlin","given":"J.S.","affiliations":[],"preferred":false,"id":437635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waser, P.M.","contributorId":66454,"corporation":false,"usgs":true,"family":"Waser","given":"P.M.","affiliations":[],"preferred":false,"id":437634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hines, J.E. 0000-0001-5478-7230","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":36885,"corporation":false,"usgs":true,"family":"Hines","given":"J.E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":437633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":437632,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70032722,"text":"70032722 - 2012 - Roost networks of northern myotis (Myotis septentrionalis) in a managed landscape","interactions":[],"lastModifiedDate":"2020-11-23T19:36:25.630698","indexId":"70032722","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Roost networks of northern myotis (Myotis septentrionalis) in a managed landscape","docAbstract":"<p><span>Maternity groups of many bat species conform to fission–fusion models and movements among diurnal roost trees and individual bats belonging to these groups use networks of roost trees. Forest disturbances may alter roost networks and characteristics of roost trees. Therefore, at the Fernow Experimental Forest in West Virginia, we examined roost tree networks of northern myotis (</span><i>Myotis septentrionalis</i><span>) in forest stands subjected to prescribed fire and in unmanipulated control treatments in 2008 and 2009. Northern myotis formed social groups whose roost areas and roost tree networks overlapped to some extent. Roost tree networks largely resembled scale-free network models, as 61% had a single central node roost tree. In control treatments, central node roost trees were in early stages of decay and surrounded by greater basal area than other trees within the networks. In prescribed fire treatments, central node roost trees were small in diameter, low in the forest canopy, and surrounded by low basal area compared to other trees in networks. Our results indicate that forest disturbances, including prescribed fire, can affect availability and distribution of roosts within roost tree networks.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2011.11.032","issn":"03781127","usgsCitation":"Johnson, J., Ford, W.M., and Edwards, J., 2012, Roost networks of northern myotis (Myotis septentrionalis) in a managed landscape: Forest Ecology and Management, v. 266, p. 223-231, https://doi.org/10.1016/j.foreco.2011.11.032.","productDescription":"9 p.","startPage":"223","endPage":"231","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":241425,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213768,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.foreco.2011.11.032"}],"country":"United States","otherGeospatial":"West 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Mark wford@usgs.gov","contributorId":3858,"corporation":false,"usgs":true,"family":"Ford","given":"W.","email":"wford@usgs.gov","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":437631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, J.W.","contributorId":62002,"corporation":false,"usgs":true,"family":"Edwards","given":"J.W.","email":"","affiliations":[],"preferred":false,"id":437630,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032695,"text":"70032695 - 2012 - Calibration of amino acid racemization (AAR) kinetics in United States mid-Atlantic Coastal Plain Quaternary mollusks using  87Sr/ 86Sr analyses: Evaluation of kinetic models and estimation of regional Late Pleistocene temperature history","interactions":[],"lastModifiedDate":"2020-11-23T19:59:30.299013","indexId":"70032695","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3216,"text":"Quaternary Geochronology","active":true,"publicationSubtype":{"id":10}},"title":"Calibration of amino acid racemization (AAR) kinetics in United States mid-Atlantic Coastal Plain Quaternary mollusks using  87Sr/ 86Sr analyses: Evaluation of kinetic models and estimation of regional Late Pleistocene temperature history","docAbstract":"<p><span>The use of amino acid&nbsp;<a title=\"Learn more about Racemization from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/racemization\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/racemization\">racemization</a>&nbsp;(AAR) for estimating ages of Quaternary fossils usually requires a combination of kinetic and effective temperature modeling or independent age calibration of analyzed samples. Because of limited availability of calibration samples, age estimates are often based on model extrapolations from single calibration points over wide ranges of D/L values. Here we present paired AAR and&nbsp;</span><sup>87</sup><span>Sr/</span><sup>86</sup><span>Sr results for Pleistocene mollusks from the North Carolina Coastal Plain, USA.&nbsp;</span><sup>87</sup><span>Sr/</span><sup>86</sup><span>Sr age estimates, derived from the lookup table of McArthur et&nbsp;al. [McArthur, J.M., Howarth, R.J., Bailey, T.R., 2001.&nbsp;<a title=\"Learn more about Strontium from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/strontium\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/strontium\">Strontium</a>&nbsp;isotopic stratigraphy: LOWESS version 3: best fit to the marine Sr-isotopic curve for 0–509 Ma and accompanying Look-up table for deriving numerical age. Journal of Geology 109, 155–169], provide independent age calibration over the full range of amino acid D/L values, thereby allowing comparisons of alternative kinetic models for seven amino acids. The often-used parabolic kinetic model is found to be insufficient to explain the pattern of racemization, although the kinetic pathways for valine racemization and isoleucine epimerization can be closely approximated with this function. Logarithmic and power law regressions more accurately represent the racemization pathways for all amino acids. The reliability of a non-linear model for&nbsp;<a title=\"Learn more about Leucine from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/leucine\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/leucine\">leucine</a>&nbsp;racemization, developed and refined over the past 20 years, is confirmed by the&nbsp;</span><sup>87</sup><span>Sr/</span><sup>86</sup><span>Sr age results. This age model indicates that the subsurface record (up to 80</span><span>&nbsp;</span><span>m thick) of the North Carolina Coastal Plain spans the entire Quaternary, back to ∼2.5</span><span>&nbsp;</span><span>Ma. The calibrated kinetics derived from this age model yield an estimate of the effective temperature for the study region of 11</span><span>&nbsp;</span><span>±</span><span>&nbsp;</span><span>2</span><span>&nbsp;</span><span>°C., from which we estimate full glacial (Last Glacial Maximum – LGM) temperatures for the region on the order of 7–10</span><span>&nbsp;</span><span>°C cooler than present. These temperatures compare favorably with independent&nbsp;<a title=\"Learn more about Paleoclimate from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/paleoclimate\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/paleoclimate\">paleoclimate</a>&nbsp;information for the region.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.quageo.2011.09.005","issn":"18711014","usgsCitation":"Wehmiller, J., Harris, W., Boutin, B., and Farrell, K., 2012, Calibration of amino acid racemization (AAR) kinetics in United States mid-Atlantic Coastal Plain Quaternary mollusks using  87Sr/ 86Sr analyses: Evaluation of kinetic models and estimation of regional Late Pleistocene temperature history: Quaternary Geochronology, v. 7, no. 1, p. 21-36, https://doi.org/10.1016/j.quageo.2011.09.005.","productDescription":"16 p.","startPage":"21","endPage":"36","costCenters":[],"links":[{"id":241528,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213863,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.quageo.2011.09.005"}],"country":"United States","state":"Delaware, Florida, Georgia, Maryland, New Jersey, North Carolina, South Carolina, Virginia,","otherGeospatial":"United States Atlantic Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.990234375,\n              29.611670115197377\n            ],\n            [\n              -82.44140625,\n              24.766784522874453\n            ],\n            [\n              -80.85937499999999,\n              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29.611670115197377\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f316e4b0c8380cd4b5bb","contributors":{"authors":[{"text":"Wehmiller, J.F.","contributorId":37891,"corporation":false,"usgs":false,"family":"Wehmiller","given":"J.F.","email":"","affiliations":[],"preferred":false,"id":437492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, W.B.","contributorId":6635,"corporation":false,"usgs":true,"family":"Harris","given":"W.B.","email":"","affiliations":[],"preferred":false,"id":437490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boutin, B.S.","contributorId":18186,"corporation":false,"usgs":true,"family":"Boutin","given":"B.S.","email":"","affiliations":[],"preferred":false,"id":437491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farrell, K.M.","contributorId":106573,"corporation":false,"usgs":true,"family":"Farrell","given":"K.M.","email":"","affiliations":[],"preferred":false,"id":437493,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70032694,"text":"70032694 - 2012 - Incidence of adult brain cancers is higher in countries where the protozoan parasite <i>Toxoplasma gondii</i> is common","interactions":[],"lastModifiedDate":"2014-09-18T13:28:00","indexId":"70032694","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1028,"text":"Biology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Incidence of adult brain cancers is higher in countries where the protozoan parasite <i>Toxoplasma gondii</i> is common","docAbstract":"We explored associations between the common protozoan parasite <i>Toxoplasma gondii</i> and brain cancers in human populations. We predicted that <i>T. gondii</i> could increase the risk of brain cancer because it is a long-lived parasite that encysts in the brain, where it provokes inflammation and inhibits apoptosis. We used a medical geography approach based on the national incidence of brain cancers and seroprevalence of <i>T. gondii</i>. We corrected reports of incidence for national gross domestic product because wealth probably increases the ability to detect cancer. We also included gender, cell phone use and latitude as variables in our initial models. Prevalence of <i>T. gondii</i> explained 19 per cent of the residual variance in brain cancer incidence after controlling for the positive effects of gross domestic product and latitude among nations. Infection with <i>T. gondii</i> was associated with a 1.8-fold increase in the risk of brain cancers across the range of <i>T. gondii</i> prevalence in our dataset (4–67%). These results, though correlational, suggest that <i>T. gondii</i> should be investigated further as a possible oncogenic pathogen of humans.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biology Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Royal Society","publisherLocation":"London","doi":"10.1098/rsbl.2011.0588","issn":"17449561","usgsCitation":"Thomas, F., Lafferty, K.D., Brodeur, J., Elguero, E., Gauthier-Clerc, M., and Misse, D., 2012, Incidence of adult brain cancers is higher in countries where the protozoan parasite <i>Toxoplasma gondii</i> is common: Biology Letters, v. 8, no. 1, p. 101-103, https://doi.org/10.1098/rsbl.2011.0588.","productDescription":"3 p.","startPage":"101","endPage":"103","numberOfPages":"3","costCenters":[],"links":[{"id":474734,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1098/rsbl.2011.0588","text":"External Repository"},{"id":241527,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213862,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1098/rsbl.2011.0588"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-07-27","publicationStatus":"PW","scienceBaseUri":"505a39d5e4b0c8380cd61a64","contributors":{"authors":[{"text":"Thomas, Frederic","contributorId":57275,"corporation":false,"usgs":true,"family":"Thomas","given":"Frederic","email":"","affiliations":[],"preferred":false,"id":437487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":437484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brodeur, Jacques","contributorId":47987,"corporation":false,"usgs":true,"family":"Brodeur","given":"Jacques","email":"","affiliations":[],"preferred":false,"id":437486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elguero, Eric","contributorId":80909,"corporation":false,"usgs":true,"family":"Elguero","given":"Eric","email":"","affiliations":[],"preferred":false,"id":437489,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gauthier-Clerc, Michel","contributorId":59639,"corporation":false,"usgs":true,"family":"Gauthier-Clerc","given":"Michel","email":"","affiliations":[],"preferred":false,"id":437488,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Misse, Dorothee","contributorId":29227,"corporation":false,"usgs":true,"family":"Misse","given":"Dorothee","email":"","affiliations":[],"preferred":false,"id":437485,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70032661,"text":"70032661 - 2012 - Climatic forcing of Quaternary deep-sea benthic communities in the North Pacific Ocean","interactions":[],"lastModifiedDate":"2013-04-21T16:54:18","indexId":"70032661","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3001,"text":"Paleobiology","active":true,"publicationSubtype":{"id":10}},"title":"Climatic forcing of Quaternary deep-sea benthic communities in the North Pacific Ocean","docAbstract":"There is growing evidence that changes in deep-sea benthic ecosystems are modulated by climate changes, but most evidence to date comes from the North Atlantic Ocean. Here we analyze new ostracod and published foraminiferal records for the last 250,000 years on Shatsky Rise in the North Pacific Ocean. Using linear models, we evaluate statistically the ability of environmental drivers (temperature, productivity, and seasonality of productivity) to predict changes in faunal diversity, abundance, and composition. These microfossil data show glacial-interglacial shifts in overall abundances and species diversities that are low during glacial intervals and high during interglacials. These patterns replicate those previously documented in the North Atlantic Ocean, suggesting that the climatic forcing of the deep-sea ecosystem is widespread, and possibly global in nature. However, these results also reveal differences with prior studies that probably reflect the isolated nature of Shatsky Rise as a remote oceanic plateau. Ostracod assemblages on Shatsky Rise are highly endemic but of low diversity, consistent with the limited dispersal potential of these animals. Benthic foraminifera, by contrast, have much greater dispersal ability and their assemblages at Shatsky Rise show diversities typical for deep-sea faunas in other regions. Statistical analyses also reveal ostracod-foraminferal differences in relationships between environmental drivers and biotic change. Rarefied diversity is best explained as a hump-shaped function of surface productivity in ostracods, but as having a weak and positive relationship with temperature in foraminifera. Abundance shows a positive relationship with both productivity and seasonality of productivity in foraminifera, and a hump-shaped relationship with productivity in ostracods. Finally, species composition in ostracods is influenced by both temperature and productivity, but only a temperature effect is evident in foraminifera. Though complex in detail, the global-scale link between deep-sea ecosystems and Quaternary climate changes underscores the importance of the interaction between the physical and biological components of paleoceanographical research for better understanding the history of the biosphere.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Paleobiology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Paleontological Society","publisherLocation":"http://www.paleosoc.org/","doi":"10.1666/10068.1","issn":"00948373","usgsCitation":"Yasuhara, M., Hunt, G., Cronin, T.M., Hokanishi, N., Kawahata, H., Tsujimoto, A., and Ishitake, M., 2012, Climatic forcing of Quaternary deep-sea benthic communities in the North Pacific Ocean: Paleobiology, v. 38, no. 1, p. 162-179, https://doi.org/10.1666/10068.1.","productDescription":"18 p.","startPage":"162","endPage":"179","costCenters":[],"links":[{"id":213894,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1666/10068.1"},{"id":241562,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Pacific Ocean","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 128.7,-85.6 ], [ 128.7,58.2 ], [ -66.5,58.2 ], [ -66.5,-85.6 ], [ 128.7,-85.6 ] ] ] } } ] }","volume":"38","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f666e4b0c8380cd4c737","contributors":{"authors":[{"text":"Yasuhara, Moriaki","contributorId":37935,"corporation":false,"usgs":true,"family":"Yasuhara","given":"Moriaki","affiliations":[],"preferred":false,"id":437332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, G.","contributorId":97699,"corporation":false,"usgs":true,"family":"Hunt","given":"G.","email":"","affiliations":[],"preferred":false,"id":437337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cronin, T. M. 0000-0002-2643-0979","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":42613,"corporation":false,"usgs":true,"family":"Cronin","given":"T.","email":"","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":false,"id":437333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hokanishi, N.","contributorId":34331,"corporation":false,"usgs":true,"family":"Hokanishi","given":"N.","email":"","affiliations":[],"preferred":false,"id":437331,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kawahata, H.","contributorId":90549,"corporation":false,"usgs":true,"family":"Kawahata","given":"H.","email":"","affiliations":[],"preferred":false,"id":437336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tsujimoto, Akira","contributorId":58448,"corporation":false,"usgs":true,"family":"Tsujimoto","given":"Akira","email":"","affiliations":[],"preferred":false,"id":437335,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ishitake, M.","contributorId":47988,"corporation":false,"usgs":true,"family":"Ishitake","given":"M.","email":"","affiliations":[],"preferred":false,"id":437334,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70032662,"text":"70032662 - 2012 - Response of an algal assemblage to nutrient enrichment and shading in a Hawaiian stream","interactions":[],"lastModifiedDate":"2019-12-04T06:30:59","indexId":"70032662","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Response of an algal assemblage to nutrient enrichment and shading in a Hawaiian stream","docAbstract":"<p>To investigate the effects of nitrate enrichment, phosphate enrichment, and light availability on benthic algae, nutrient-diffusing clay flowerpots were colonized with algae at two sites in a Hawaiian stream during spring and autumn 2002 using a randomized factorial design. The algal assemblage that developed under the experimental conditions was investigated by determining biomass (ash-free dry mass and chlorophyll a concentrations) and composition of the diatom assemblage. In situ pulse amplitude-modulated fluorometry was also used to model photosynthetic rate of the algal assemblage. Algal biomass and maximum photosynthetic rate were significantly higher at the unshaded site than at the shaded site. These parameters were higher at the unshaded site with either nitrate, or to a lesser degree, nitrate plus phosphate enrichment. Analysis of similarity of diatom assemblages showed significant differences between shaded and unshaded sites, as well as between spring and autumn experiments, but not between nutrient treatments. However, several individual species of diatoms responded significantly to nitrate enrichment. These results demonstrate that light availability (shaded vs. unshaded) is the primary limiting factor to algal growth in this stream, with nitrogen as a secondary limiting factor.&nbsp;</p>","language":"English","publisher":"Springer","doi":"10.1007/s10750-011-0947-2","issn":"00188158","usgsCitation":"Stephens, S., Brasher, A., and Smith, C., 2012, Response of an algal assemblage to nutrient enrichment and shading in a Hawaiian stream: Hydrobiologia, v. 683, no. 1, p. 135-150, https://doi.org/10.1007/s10750-011-0947-2.","productDescription":"16 p.","startPage":"135","endPage":"150","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":501107,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://stars.library.ucf.edu/facultybib2010/3349","text":"External Repository"},{"id":241563,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Oahu, Waihee Stream","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -157.8955078125,\n              21.417276156993662\n            ],\n            [\n              -157.77740478515625,\n              21.417276156993662\n            ],\n            [\n              -157.77740478515625,\n              21.49396356306447\n            ],\n            [\n              -157.8955078125,\n              21.49396356306447\n            ],\n            [\n              -157.8955078125,\n              21.417276156993662\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"683","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-11-19","publicationStatus":"PW","scienceBaseUri":"505aaa2fe4b0c8380cd861bc","contributors":{"authors":[{"text":"Stephens, S.H.","contributorId":57276,"corporation":false,"usgs":true,"family":"Stephens","given":"S.H.","email":"","affiliations":[],"preferred":false,"id":437339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brasher, A.M.D.","contributorId":8213,"corporation":false,"usgs":true,"family":"Brasher","given":"A.M.D.","email":"","affiliations":[],"preferred":false,"id":437338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, C.M.","contributorId":93670,"corporation":false,"usgs":true,"family":"Smith","given":"C.M.","email":"","affiliations":[],"preferred":false,"id":437340,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032691,"text":"70032691 - 2012 - Increased atmospheric deposition of mercury in reference lakes near major urban areas","interactions":[],"lastModifiedDate":"2020-11-24T16:50:10.031699","indexId":"70032691","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Increased atmospheric deposition of mercury in reference lakes near major urban areas","docAbstract":"<p><span>Atmospheric deposition of Hg is the predominant pathway for Hg to reach sensitive ecosystems, but the importance of emissions on near-field deposition remains unclear. To better understand spatial variability in Hg deposition, mercury concentrations were analyzed in sediment cores from 12 lakes with undeveloped watersheds near to (&lt;50&nbsp;km) and remote from (&gt;150&nbsp;km) several major urban areas in the United States. Background and focusing corrected Hg fluxes and flux ratios (modern to background) in the near-urban lakes (68&nbsp;±&nbsp;6.9&nbsp;μg&nbsp;m</span><sup>−2</sup><span>&nbsp;yr</span><sup>−1</sup><span>&nbsp;and 9.8&nbsp;±&nbsp;4.8, respectively) greatly exceed those in the remote lakes (14&nbsp;±&nbsp;9.3&nbsp;μg&nbsp;m</span><sup>−2</sup><span>&nbsp;yr</span><sup>−1</sup><span>&nbsp;and 3.5&nbsp;±&nbsp;1.0) and the fluxes are strongly related to distance from the nearest major urban area (</span><i>r</i><sup>2</sup><span>&nbsp;=&nbsp;0.87) and to population and Hg emissions within 50–100&nbsp;km of the lakes. Comparison to monitored wet deposition suggests that dry deposition is a major contributor of Hg to lakes near major urban areas.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2011.11.003","usgsCitation":"Van Metre, P., 2012, Increased atmospheric deposition of mercury in reference lakes near major urban areas: Environmental Pollution, v. 162, p. 209-215, https://doi.org/10.1016/j.envpol.2011.11.003.","productDescription":"7 p.","startPage":"209","endPage":"215","costCenters":[],"links":[{"id":241458,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213799,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envpol.2011.11.003"}],"country":"United 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,{"id":70032635,"text":"70032635 - 2012 - Mineral parageneses, regional architecture, and tectonic evolution of Franciscan metagraywackes, Cape Mendocino-Garberville-Covelo 30' x 60' quadrangles, northwest California","interactions":[],"lastModifiedDate":"2017-09-01T09:27:38","indexId":"70032635","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Mineral parageneses, regional architecture, and tectonic evolution of Franciscan metagraywackes, Cape Mendocino-Garberville-Covelo 30' x 60' quadrangles, northwest California","docAbstract":"<p><span>The Franciscan Complex is a classic subduction-zone assemblage. In northwest California, it comprises a stack of west vergent thrust sheets: westernmost Eastern Belt outliers; Central Belt m&eacute;lange; Coastal Belt Yager terrane; Coastal Belt Coastal terrane; Coastal Belt King Range/False Cape terranes. We collected samples and determined P-T conditions of recrystallization for 88 medium-fine-grained metasandstones to assess their subduction-exhumation histories and assembly of the host allochthons. Feebly recrystallized Yager, Coastal, and King Range strata retain clear detrital features. Scattered neoblastic prehnite occurs in several Coastal terrane metasandstones; traces of possible pumpellyite are present in three Yager metaclastic rocks. Pumpellyite &plusmn; lawsonite &plusmn; aragonite-bearing Central Belt metasandstones are moderately deformed and reconstituted. Intensely contorted, thoroughly recrystallized Eastern Belt affinity quartzose metagraywackes contain lawsonite + jadeitic pyroxene &plusmn; aragonite &plusmn; glaucophane. We microprobed neoblastic phases in 23 rocks, documenting mineral parageneses that constrain the tectonic accretion and metamorphic P-T evolution of these sheets. Quasi-stable mineral assemblages typify Eastern Belt metasandstones, but mm-sized domains in the Central and Coastal belt rocks failed to achieve chemical equilibrium. Eastern Belt slabs rose from subduction depths approaching 25&ndash;30&nbsp;km, whereas structurally lower Central Belt m&eacute;langes returned from &sim;15&ndash;18&nbsp;km. Coastal Belt assemblages suggest burial depths less than 5&ndash;8&nbsp;km. Eastern and Central belt allochthons sequentially decoupled from the downgoing oceanic lithosphere and ascended into the accretionary margin; K-feldspar-rich Coastal Belt rocks were stranded along the continental edge without undergoing appreciable subduction, probably during Paleogene unroofing of the older, deeply subducted units of the Franciscan Complex in east-vergent crustal wedges.</span></p>","language":"English","publisher":"AGU","doi":"10.1029/2011TC002987","issn":"02787407","usgsCitation":"Ernst, W., and McLaughlin, R.J., 2012, Mineral parageneses, regional architecture, and tectonic evolution of Franciscan metagraywackes, Cape Mendocino-Garberville-Covelo 30' x 60' quadrangles, northwest California: Tectonics, v. 31, no. 1, Article TC1001, https://doi.org/10.1029/2011TC002987.","productDescription":"Article TC1001","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033454","costCenters":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":241657,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213979,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2011TC002987"}],"country":"United States","state":"California","otherGeospatial":"Cape Mendocino-Garberville-Covelo","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.53002929687499,\n              39.2407625100131\n            ],\n            [\n              -124.53002929687499,\n              40.455307212131494\n            ],\n            [\n              -122.76123046875,\n              40.455307212131494\n            ],\n            [\n              -122.76123046875,\n              39.2407625100131\n            ],\n            [\n              -124.53002929687499,\n              39.2407625100131\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"31","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-12","publicationStatus":"PW","scienceBaseUri":"505a57a1e4b0c8380cd6ddd0","contributors":{"authors":[{"text":"Ernst, W. G.","contributorId":18456,"corporation":false,"usgs":true,"family":"Ernst","given":"W. G.","affiliations":[],"preferred":false,"id":437158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLaughlin, Robert J. 0000-0002-4390-2288 rjmcl@usgs.gov","orcid":"https://orcid.org/0000-0002-4390-2288","contributorId":1428,"corporation":false,"usgs":true,"family":"McLaughlin","given":"Robert","email":"rjmcl@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":437159,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70032636,"text":"70032636 - 2012 - Photodissolution of soil organic matter","interactions":[],"lastModifiedDate":"2020-11-24T18:25:48.824762","indexId":"70032636","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"Photodissolution of soil organic matter","docAbstract":"<p><span>Sunlight has been shown to enhance loss of organic matter from aquatic sediments and terrestrial plant litter, so we tested for similar reactions in mineral soil horizons. Losses of up to a third of particulate organic carbon occurred after continuous exposure to full-strength sunlight for dozens of hours, with similar amounts appearing as photodissolved organic carbon. Nitrogen dissolved similarly, appearing partly as ammonium. Modified experiments with interruption of irradiation to include extended dark incubation periods increased loss of total organic carbon, implying remineralization by some combination of light and microbes. These photodissolution reactions respond strongly to water content, with reaction extent under air-dry to fully wet conditions increasing by a factor of 3–4 fold. Light limitation was explored using lamp intensity and soil depth experiments. Reaction extent varied linearly with lamp intensity. Depth experiments indicate that attenuation of reaction occurs within the top tens to hundreds of micrometers of soil depth. Our data allow only order-of-magnitude extrapolations to field conditions, but suggest that this type of reaction could induce loss of 10–20% of soil organic carbon in the top 10</span><span>&nbsp;</span><span>cm horizon over a century. It may therefore have contributed to historical losses of soil carbon via agriculture, and should be considered in soil management on similar time scales.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2011.11.030","issn":"00167061","usgsCitation":"Mayer, L., Thornton, K., Schick, L., Jastrow, J., and Harden, J.W., 2012, Photodissolution of soil organic matter: Geoderma, v. 170, p. 314-321, https://doi.org/10.1016/j.geoderma.2011.11.030.","productDescription":"8 p.","startPage":"314","endPage":"321","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":241658,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213980,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geoderma.2011.11.030"}],"volume":"170","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a78c7e4b0c8380cd7879f","contributors":{"authors":[{"text":"Mayer, L.M.","contributorId":56455,"corporation":false,"usgs":true,"family":"Mayer","given":"L.M.","email":"","affiliations":[],"preferred":false,"id":437161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thornton, K.R.","contributorId":60030,"corporation":false,"usgs":true,"family":"Thornton","given":"K.R.","email":"","affiliations":[],"preferred":false,"id":437162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schick, L.L.","contributorId":64040,"corporation":false,"usgs":true,"family":"Schick","given":"L.L.","email":"","affiliations":[],"preferred":false,"id":437163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jastrow, J.D.","contributorId":89730,"corporation":false,"usgs":true,"family":"Jastrow","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":437164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":437160,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70032604,"text":"70032604 - 2012 - Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system","interactions":[],"lastModifiedDate":"2017-11-05T22:24:26","indexId":"70032604","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system","docAbstract":"<div id=\"aep-abstract-id30\" class=\"abstract author\" lang=\"en\"><div id=\"aep-abstract-sec-id31\"><p id=\"sp010\"><span>The coupled ocean–atmosphere–wave–sediment transport (COAWST) modeling system was used to investigate atmosphere–ocean–wave interactions in November 2009 during Hurricane Ida and its subsequent evolution to Nor’Ida, which was one of the most costly storm systems of the past two decades. One interesting aspect of this event is that it included two unique atmospheric extreme conditions, a hurricane and a nor’easter storm, which developed in regions with different oceanographic characteristics. Our modeled results were compared with several data sources, including GOES satellite infrared data, JASON-1 and JASON-2 altimeter data, CODAR measurements, and wave and tidal information from the National Data Buoy Center (NDBC) and the National Tidal Database. By performing a series of numerical runs, we were able to isolate the effect of the interaction terms between the atmosphere (modeled with Weather Research and Forecasting, the WRF model), the ocean (modeled with Regional Ocean Modeling System (ROMS)), and the wave propagation and generation model (modeled with Simulating Waves Nearshore (SWAN)). Special attention was given to the role of the ocean surface roughness. Three different ocean roughness closure models were analyzed: </span>DGHQ (which is based on wave age), TY2001 (which is based on wave steepness), and OOST (which considers both the effects of wave age and steepness). Including the ocean roughness in the atmospheric module improved the wind intensity estimation and therefore also the wind waves, surface currents, and storm surge amplitude. For example, during the passage of Hurricane Ida through the Gulf of Mexico, the wind speeds were reduced due to wave-induced ocean roughness, resulting in better agreement with the measured winds. During Nor’Ida, including the wave-induced surface roughness changed the form and dimension of the main low pressure cell, affecting the intensity and direction of the winds. The combined wave age- and wave steepness-based parameterization (OOST) provided the best results for wind and wave growth prediction. However, the best agreement between the measured (CODAR) and computed surface currents and storm surge values was obtained with the wave steepness-based roughness parameterization (TY2001), although the differences obtained with respect to DGHQ were not significant. The influence of sea surface temperature (SST) fields on the atmospheric boundary layer dynamics was examined; in particular, we evaluated how the SST affects wind wave generation, surface currents and storm surges. The integrated hydrograph and integrated wave height, parameters that are highly correlated with the storm damage potential, were found to be highly sensitive to the ocean surface roughness parameterization.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocemod.2011.12.008","issn":"14635003","usgsCitation":"Olabarrieta, M., Warner, J., Armstrong, B., Zambon, J.B., and He, R., 2012, Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system: Ocean Modelling, v. 43-44, p. 112-137, https://doi.org/10.1016/j.ocemod.2011.12.008.","productDescription":"26 p.","startPage":"112","endPage":"137","costCenters":[],"links":[{"id":474640,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/5124","text":"External Repository"},{"id":241690,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43-44","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6c99e4b0c8380cd74ced","contributors":{"authors":[{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":81631,"corporation":false,"usgs":true,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":437025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":437024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Armstrong, Brandy N. barmstrong@usgs.gov","contributorId":5897,"corporation":false,"usgs":true,"family":"Armstrong","given":"Brandy N.","email":"barmstrong@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":437023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zambon, Joseph B.","contributorId":8222,"corporation":false,"usgs":true,"family":"Zambon","given":"Joseph","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":437026,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"He, Ruoying","contributorId":58965,"corporation":false,"usgs":true,"family":"He","given":"Ruoying","affiliations":[],"preferred":false,"id":437027,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70032538,"text":"70032538 - 2012 - Species traits and environmental conditions govern the relationship between biodiversity effects across trophic levels","interactions":[],"lastModifiedDate":"2020-11-30T22:06:47.321118","indexId":"70032538","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Species traits and environmental conditions govern the relationship between biodiversity effects across trophic levels","docAbstract":"<p><span>Changing environments can have divergent effects on biodiversity–ecosystem function relationships at alternating trophic levels. Freshwater mussels fertilize stream foodwebs through nutrient excretion, and mussel species-specific excretion rates depend on environmental conditions. We asked how differences in mussel diversity in varying environments influence the dynamics between primary producers and consumers. We conducted field experiments manipulating mussel richness under summer (low flow, high temperature) and fall (moderate flow and temperature) conditions, measured nutrient limitation, algal biomass and grazing chironomid abundance, and analyzed the data with non-transgressive overyielding and tripartite biodiversity partitioning analyses. Algal biomass and chironomid abundance were best explained by trait-independent complementarity among mussel species, but the relationship between biodiversity effects across trophic levels (algae and grazers) depended on seasonal differences in mussel species’ trait expression (nutrient excretion and activity level). Both species identity and overall diversity effects were related to the magnitude of nutrient limitation. Our results demonstrate that biodiversity of a resource-provisioning (nutrients and habitat) group of species influences foodweb dynamics and that understanding species traits and environmental context are important for interpreting biodiversity experiments.</span></p>","language":"English","publisher":"Springer- Verlag","doi":"10.1007/s00442-011-2110-1","issn":"00298549","usgsCitation":"Spooner, D., Vaughn, C., and Galbraith, H., 2012, Species traits and environmental conditions govern the relationship between biodiversity effects across trophic levels: Oecologia, v. 168, no. 2, p. 533-548, https://doi.org/10.1007/s00442-011-2110-1.","productDescription":"16 p.","startPage":"533","endPage":"548","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":241724,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214037,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00442-011-2110-1"}],"volume":"168","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-09-08","publicationStatus":"PW","scienceBaseUri":"505b9514e4b08c986b31ad22","contributors":{"authors":[{"text":"Spooner, D.E.","contributorId":26528,"corporation":false,"usgs":true,"family":"Spooner","given":"D.E.","email":"","affiliations":[],"preferred":false,"id":436711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vaughn, C.C.","contributorId":40027,"corporation":false,"usgs":true,"family":"Vaughn","given":"C.C.","email":"","affiliations":[],"preferred":false,"id":436712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galbraith, H.S. 0000-0003-3704-3517","orcid":"https://orcid.org/0000-0003-3704-3517","contributorId":94509,"corporation":false,"usgs":true,"family":"Galbraith","given":"H.S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":436713,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032644,"text":"70032644 - 2012 - Wolf population dynamics in the U.S. Northern Rocky Mountains are affected by recruitment and human-caused mortality","interactions":[],"lastModifiedDate":"2022-04-04T15:19:04.961432","indexId":"70032644","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Wolf population dynamics in the U.S. Northern Rocky Mountains are affected by recruitment and human-caused mortality","docAbstract":"<p>Reliable analyses can help wildlife managers make good decisions, which are particularly critical for controversial decisions such as wolf (Canis lupus) harvest. Creel and Rotella (2010) recently predicted substantial population declines in Montana wolf populations due to harvest, in contrast to predictions made by Montana Fish, Wildlife and Parks (MFWP). We replicated their analyses considering only those years in which field monitoring was consistent, and we considered the effect of annual variation in recruitment on wolf population growth. Rather than assuming constant rates, we used model selection methods to evaluate and incorporate models of factors driving recruitment and human-caused mortality rates in wolf populations in the Northern Rocky Mountains. Using data from 27 area-years of intensive wolf monitoring, we show that variation in both recruitment and human-caused mortality affect annual wolf population growth rates and that human-caused mortality rates have increased with the sizes of wolf populations. We document that recruitment rates have decreased over time, and we speculate that rates have decreased with increasing population sizes and/or that the ability of current field resources to document recruitment rates has recently become less successful as the number of wolves in the region has increased. Estimates of positive wolf population growth in Montana from our top models are consistent with field observations and estimates previously made by MFWP for 2008–2010, whereas the predictions for declining wolf populations of Creel and Rotella (2010) are not. Familiarity with limitations of raw data, obtained first-hand or through consultation with scientists who collected the data, helps generate more reliable inferences and conclusions in analyses of publicly available datasets. Additionally, development of efficient monitoring methods for wolves is a pressing need, so that analyses such as ours will be possible in future years when fewer resources will be available for monitoring.</p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.201","issn":"0022541X","usgsCitation":"Gude, J., Mitchell, M., Russell, R.E., Sime, C., Bangs, E., Mech, L., and Ream, R., 2012, Wolf population dynamics in the U.S. Northern Rocky Mountains are affected by recruitment and human-caused mortality: Journal of Wildlife Management, v. 76, no. 1, p. 108-118, https://doi.org/10.1002/jwmg.201.","productDescription":"11 p.","startPage":"108","endPage":"118","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":241289,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213642,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.201"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"The NWMT, CIEPA, and GYEPA federal wolf recovery area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.2041015625,\n              45.042478050891546\n            ],\n            [\n              -109.57763671875,\n              46.042735653846506\n            ],\n            [\n              -112.60986328125,\n              45.98169518512228\n            ],\n            [\n              -113.44482421875,\n              45.30580259943578\n            ],\n            [\n              -112.939453125,\n              44.11914151643737\n            ],\n            [\n              -110.98388671874999,\n              43.929549935614595\n            ],\n            [\n              -108.984375,\n              44.18220395771566\n            ],\n            [\n              -109.2041015625,\n              45.042478050891546\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"76","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-08-03","publicationStatus":"PW","scienceBaseUri":"505bd187e4b08c986b32f497","contributors":{"authors":[{"text":"Gude, J.A.","contributorId":101092,"corporation":false,"usgs":true,"family":"Gude","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":437242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, M.S.","contributorId":26724,"corporation":false,"usgs":true,"family":"Mitchell","given":"M.S.","email":"","affiliations":[],"preferred":false,"id":437236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":437237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sime, C.A.","contributorId":54413,"corporation":false,"usgs":true,"family":"Sime","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":437239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bangs, E.E.","contributorId":49614,"corporation":false,"usgs":true,"family":"Bangs","given":"E.E.","email":"","affiliations":[],"preferred":false,"id":437238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mech, L.D. 0000-0003-3944-7769","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":75466,"corporation":false,"usgs":false,"family":"Mech","given":"L.D.","email":"","affiliations":[],"preferred":false,"id":437240,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ream, R.R.","contributorId":93154,"corporation":false,"usgs":true,"family":"Ream","given":"R.R.","email":"","affiliations":[],"preferred":false,"id":437241,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70032689,"text":"70032689 - 2012 - Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern","interactions":[],"lastModifiedDate":"2020-11-24T17:21:03.47963","indexId":"70032689","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"title":"Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern","docAbstract":"<p><span>The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially‐explicit, individual‐based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation‐by‐distance, isolation‐by‐barrier, and isolation‐by‐landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non‐equilibrium conditions after introduction of isolation‐by‐landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel&nbsp;</span><i>r</i><span>&nbsp;correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel&nbsp;</span><i>r</i><span>, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel&nbsp;</span><i>r</i><span>&nbsp;estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.</span></p>","language":"English","publisher":"Blackwell","doi":"10.1111/j.1755-0998.2011.03077.x","issn":"1755098X","usgsCitation":"Landguth, E., Fedy, B., Oyler-McCance, S.J., Garey, A., Emel, S., Mumma, M., Wagner, H., Fortin, M., and Cushman, S., 2012, Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern: Molecular Ecology Resources, v. 12, no. 2, p. 276-284, https://doi.org/10.1111/j.1755-0998.2011.03077.x.","productDescription":"9 p.","startPage":"276","endPage":"284","numberOfPages":"9","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":241423,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213766,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1755-0998.2011.03077.x"}],"volume":"12","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-10-02","publicationStatus":"PW","scienceBaseUri":"505a07bce4b0c8380cd517e2","contributors":{"authors":[{"text":"Landguth, E.L.","contributorId":30049,"corporation":false,"usgs":true,"family":"Landguth","given":"E.L.","affiliations":[],"preferred":false,"id":437459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fedy, B.C.","contributorId":35427,"corporation":false,"usgs":true,"family":"Fedy","given":"B.C.","email":"","affiliations":[],"preferred":false,"id":437460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":437462,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garey, A.L.","contributorId":37546,"corporation":false,"usgs":true,"family":"Garey","given":"A.L.","affiliations":[],"preferred":false,"id":437461,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Emel, S.L.","contributorId":101890,"corporation":false,"usgs":true,"family":"Emel","given":"S.L.","affiliations":[],"preferred":false,"id":437465,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mumma, M.","contributorId":108323,"corporation":false,"usgs":true,"family":"Mumma","given":"M.","email":"","affiliations":[],"preferred":false,"id":437466,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wagner, H.H.","contributorId":26526,"corporation":false,"usgs":true,"family":"Wagner","given":"H.H.","email":"","affiliations":[],"preferred":false,"id":437458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fortin, M.-J.","contributorId":96489,"corporation":false,"usgs":true,"family":"Fortin","given":"M.-J.","email":"","affiliations":[],"preferred":false,"id":437464,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cushman, S.A.","contributorId":92876,"corporation":false,"usgs":true,"family":"Cushman","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":437463,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70032602,"text":"70032602 - 2012 - Hierarchy in factors affecting fish biodiversity in floodplain lakes of the Mississippi Alluvial Valley","interactions":[],"lastModifiedDate":"2020-11-30T18:35:45.60633","indexId":"70032602","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchy in factors affecting fish biodiversity in floodplain lakes of the Mississippi Alluvial Valley","docAbstract":"<p><span>River-floodplain ecosystems offer some of the most diverse and dynamic environments in the world. Accordingly, floodplain habitats harbor diverse fish assemblages. Fish biodiversity in floodplain lakes may be influenced by multiple variables operating on disparate scales, and these variables may exhibit a hierarchical organization depending on whether one variable governs another. In this study, we examined the interaction between primary variables descriptive of floodplain lake large-scale features, suites of secondary variables descriptive of water quality and primary productivity, and a set of tertiary variables descriptive of fish biodiversity across a range of floodplain lakes in the Mississippi Alluvial Valley of Mississippi and Arkansas (USA). Lakes varied considerably in their representation of primary, secondary, and tertiary variables. Multivariate direct gradient analyses indicated that lake maximum depth and the percentage of agricultural land surrounding a lake were the most important factors controlling variation in suites of secondary and tertiary variables, followed to a lesser extent by lake surface area. Fish biodiversity was generally greatest in large, deep lakes with lower proportions of watershed agricultural land. Our results may help foster a holistic approach to floodplain lake management and suggest the framework for a feedback model wherein primary variables can be manipulated for conservation and restoration purposes and secondary and tertiary variables can be used to monitor the success of such efforts.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s10641-011-9923-y","issn":"03781909","usgsCitation":"Dembkowski, D., and Miranda, L., 2012, Hierarchy in factors affecting fish biodiversity in floodplain lakes of the Mississippi Alluvial Valley: Environmental Biology of Fishes, v. 93, no. 3, p. 357-368, https://doi.org/10.1007/s10641-011-9923-y.","productDescription":"12 p.","startPage":"357","endPage":"368","costCenters":[],"links":[{"id":241656,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213978,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10641-011-9923-y"}],"country":"United States","state":"Arkansas, Mississippi","otherGeospatial":"Lower Mississippi Alluvial Valley region of Mississippi and Arkansas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.285400390625,\n              32.690243035492266\n            ],\n            [\n              -90.845947265625,\n              32.759562025650126\n            ],\n            [\n              -90.7855224609375,\n              33.902336404480685\n            ],\n            [\n              -90.2801513671875,\n              34.67839374011646\n            ],\n            [\n              -89.84069824218749,\n              35.44724605551148\n            ],\n            [\n              -90.5877685546875,\n              35.51881428123057\n            ],\n            [\n              -91.3568115234375,\n              33.911454454267606\n            ],\n            [\n              -91.285400390625,\n              32.690243035492266\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"93","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-09-09","publicationStatus":"PW","scienceBaseUri":"505a30a7e4b0c8380cd5d822","contributors":{"authors":[{"text":"Dembkowski, D.J.","contributorId":31995,"corporation":false,"usgs":true,"family":"Dembkowski","given":"D.J.","affiliations":[],"preferred":false,"id":437014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, L.E.","contributorId":58406,"corporation":false,"usgs":true,"family":"Miranda","given":"L.E.","affiliations":[],"preferred":false,"id":437015,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70032606,"text":"70032606 - 2012 - Reducing uncertainty about objective functions in adaptive management","interactions":[],"lastModifiedDate":"2020-11-30T17:51:50.10832","indexId":"70032606","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Reducing uncertainty about objective functions in adaptive management","docAbstract":"<p><span>This paper extends the uncertainty framework of adaptive management to include uncertainty about the objectives to be used in guiding decisions. Adaptive decision making typically assumes explicit and agreed-upon objectives for management, but allows for uncertainty as to the structure of the decision process that generates change through time. Yet it is not unusual for there to be uncertainty (or disagreement) about objectives, with different stakeholders expressing different views not only about resource responses to management but also about the appropriate management objectives. In this paper I extend the treatment of uncertainty in adaptive management, and describe a stochastic structure for the joint occurrence of uncertainty about objectives as well as models, and show how adaptive decision making and the assessment of post-decision monitoring data can be used to reduce uncertainties of both kinds. Different degrees of association between model and objective uncertainty lead to different patterns of learning about objectives.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2011.11.009","issn":"03043800","usgsCitation":"Williams, B.K., 2012, Reducing uncertainty about objective functions in adaptive management: Ecological Modelling, v. 225, p. 61-65, https://doi.org/10.1016/j.ecolmodel.2011.11.009.","productDescription":"5 p.","startPage":"61","endPage":"65","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":241728,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214041,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2011.11.009"}],"volume":"225","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4a3d2e4b0e8fec6cdb9b8","contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":207067,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":437032,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70032574,"text":"70032574 - 2012 - Regional scale impacts of <i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods","interactions":[],"lastModifiedDate":"2017-11-25T14:17:42","indexId":"70032574","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","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":"Regional scale impacts of <i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods","docAbstract":"<i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) have been widely released on western U.S. rivers to control introduced shrubs in the genus <i>Tamarix</i>. Part of the motivation to control <i>Tamarix</i> is to salvage water for human use. Information is needed on the impact of beetles on <i>Tamarix</i> seasonal leaf production and subsequent water use overwide areas andmultiple cycles of annual defoliation.Herewe combine ground data with high resolution phenocam imagery and moderate resolution (Landsat) and coarser resolution (MODIS) satellite imagery to test the effects of beetles on <i>Tamarix</i> evapotranspiration (ET) and leaf phenology at sites on six western rivers. Satellite imagery covered the period 2000 to 2010 which encompassed years before and after beetle release at each study site. Phenocam images showed that beetles reduced green leaf cover of individual canopies by about 30% during a 6-8 week period in summer, but plants produced new leaves after beetles became dormant in August, and over three years no net reduction in peak summer leaf production was noted. ETwas estimated by vegetation index methods, and both Landsat and MODIS analyses showed that beetles reduced ET markedly in the first year of defoliation, but ET recovered in subsequent years. Over all six sites, ET decreased by 14% to 15% by Landsat and MODIS estimates, respectively. However, resultswere variable among sites, ranging fromno apparent effect on ET to substantial reduction in ET. Baseline ET rates before defoliation were low, 394 mmyr<sup>-1</sup> by Landsat and 314 mm yr<sup>-1</sup> by MODIS estimates (20-25% of potential ET), further constraining the amount of water that could be salvaged. Beetle-<i>Tamarix</i> interactions are in their early stage of development on this continent and it is too soon to predict the eventual extent towhich <i>Tamarix</i> populationswill be reduced. The utility of remote sensing methods for monitoring defoliation was constrained by the small area covered by each phenocamimage, the low temporal resolution of Landsat, and the lowspatial resolution ofMODIS imagery. Even combined image sets did not adequately reveal the details of the defoliation process, and remote sensing data should be combined with ground observations to develop operational monitoring protocols.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2011.11.011","issn":"00344257","usgsCitation":"Nagler, P.L., Brown, T., Hultine, K.R., van Riper, C., Bean, D., Dennison, P.E., Murray, R.S., and Glenn, E.P., 2012, Regional scale impacts of <i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods: Remote Sensing of Environment, v. 118, p. 227-240, https://doi.org/10.1016/j.rse.2011.11.011.","productDescription":"14 p.","startPage":"227","endPage":"240","numberOfPages":"14","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":241759,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214071,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2011.11.011"}],"country":"United States","state":"Colorado;Nevada;Utah;Wyoming","otherGeospatial":"Big Horn River;Humbolt River;Lower Delores River;Middle-upper Delores River;Upper Colorado River;Walker River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.0800,37.0000 ], [ -120.0800,45.0000 ], [ -106.3000,45.0000 ], [ -106.3000,37.0000 ], [ -120.0800,37.0000 ] ] ] } } ] }","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50788eb2e4b0cfc2d59f5b0d","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":436882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Tim","contributorId":17841,"corporation":false,"usgs":true,"family":"Brown","given":"Tim","affiliations":[],"preferred":false,"id":436884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hultine, Kevin R. 0000-0001-9747-6037","orcid":"https://orcid.org/0000-0001-9747-6037","contributorId":23772,"corporation":false,"usgs":true,"family":"Hultine","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":436886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":436888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bean, Daniel W.","contributorId":11016,"corporation":false,"usgs":false,"family":"Bean","given":"Daniel W.","affiliations":[{"id":16124,"text":"Colorado Department of Agriculture, Biological Pest Control","active":true,"usgs":false}],"preferred":false,"id":436883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dennison, Philip E.","contributorId":105132,"corporation":false,"usgs":true,"family":"Dennison","given":"Philip","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":436889,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murray, R. Scott","contributorId":64468,"corporation":false,"usgs":true,"family":"Murray","given":"R.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":436887,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":436885,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70032570,"text":"70032570 - 2012 - Hydrological effects of the increased CO<sub>2</sub> and climate change in the Upper Mississippi River Basin using a modified SWAT","interactions":[],"lastModifiedDate":"2013-06-04T13:52:54","indexId":"70032570","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Hydrological effects of the increased CO<sub>2</sub> and climate change in the Upper Mississippi River Basin using a modified SWAT","docAbstract":"Increased atmospheric CO<sub>2</sub> concentration and climate change may significantly impact the hydrological and meteorological processes of a watershed system. Quantifying and understanding hydrological responses to elevated ambient CO<sub>2</sub> and climate change is, therefore, critical for formulating adaptive strategies for an appropriate management of water resources. In this study, the Soil and Water Assessment Tool (SWAT) model was applied to assess the effects of increased CO<sub>2</sub> concentration and climate change in the Upper Mississippi River Basin (UMRB). The standard SWAT model was modified to represent more mechanistic vegetation type specific responses of stomatal conductance reduction and leaf area increase to elevated CO<sub>2</sub> based on physiological studies. For estimating the historical impacts of increased CO<sub>2</sub> in the recent past decades, the incremental (i.e., dynamic) rises of CO<sub>2</sub> concentration at a monthly time-scale were also introduced into the model. Our study results indicated that about 1–4% of the streamflow in the UMRB during 1986 through 2008 could be attributed to the elevated CO<sub>2</sub> concentration. In addition to evaluating a range of future climate sensitivity scenarios, the climate projections by four General Circulation Models (GCMs) under different greenhouse gas emission scenarios were used to predict the hydrological effects in the late twenty-first century (2071–2100). Our simulations demonstrated that the water yield would increase in spring and substantially decrease in summer, while soil moisture would rise in spring and decline in summer. Such an uneven distribution of water with higher variability compared to the baseline level (1961–1990) may cause an increased risk of both flooding and drought events in the basin.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Climatic Change","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10584-011-0087-8","issn":"01650009","usgsCitation":"Wu, Y., Liu, S., and Abdul-Aziz, O., 2012, Hydrological effects of the increased CO<sub>2</sub> and climate change in the Upper Mississippi River Basin using a modified SWAT: Climatic Change, v. 110, no. 3-4, p. 977-1003, https://doi.org/10.1007/s10584-011-0087-8.","productDescription":"27 p.","startPage":"977","endPage":"1003","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":241687,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214003,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10584-011-0087-8"}],"country":"United States","otherGeospatial":"Mississippi River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.0577,28.9254 ], [ -104.0577,49.38 ], [ -80.5182,49.38 ], [ -80.5182,28.9254 ], [ -104.0577,28.9254 ] ] ] } } ] }","volume":"110","issue":"3-4","noUsgsAuthors":false,"publicationDate":"2011-05-10","publicationStatus":"PW","scienceBaseUri":"505a36ace4b0c8380cd608e2","contributors":{"authors":[{"text":"Wu, Y.","contributorId":79312,"corporation":false,"usgs":true,"family":"Wu","given":"Y.","email":"","affiliations":[],"preferred":false,"id":436861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, S.","contributorId":93170,"corporation":false,"usgs":true,"family":"Liu","given":"S.","affiliations":[],"preferred":false,"id":436863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abdul-Aziz, O. I.","contributorId":91700,"corporation":false,"usgs":true,"family":"Abdul-Aziz","given":"O. I.","affiliations":[],"preferred":false,"id":436862,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032565,"text":"70032565 - 2012 - Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains","interactions":[],"lastModifiedDate":"2018-02-23T13:12:35","indexId":"70032565","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains","docAbstract":"Flux tower networks (e. g., AmeriFlux, Agriflux) provide continuous observations of ecosystem exchanges of carbon (e. g., net ecosystem exchange), water vapor (e. g., evapotranspiration), and energy between terrestrial ecosystems and the atmosphere. The long-term time series of flux tower data are essential for studying and understanding terrestrial carbon cycles, ecosystem services, and climate changes. Currently, there are 13 flux towers located within the Great Plains (GP). The towers are sparsely distributed and do not adequately represent the varieties of vegetation cover types, climate conditions, and geophysical and biophysical conditions in the GP. This study assessed how well the available flux towers represent the environmental conditions or \"ecological envelopes\" across the GP and identified optimal locations for future flux towers in the GP. Regression-based remote sensing and weather-driven net ecosystem production (NEP) models derived from different extrapolation ranges (10 and 50%) were used to identify areas where ecological conditions were poorly represented by the flux tower sites and years previously used for mapping grassland fluxes. The optimal lands suitable for future flux towers within the GP were mapped. Results from this study provide information to optimize the usefulness of future flux towers in the GP and serve as a proxy for the uncertainty of the NEP map.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landscape Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1007/s10980-011-9699-7","issn":"09212973","usgsCitation":"Gu, Y., Howard, D., Wylie, B.K., and Zhang, L., 2012, Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains: Landscape Ecology, v. 27, no. 3, p. 319-326, https://doi.org/10.1007/s10980-011-9699-7.","startPage":"319","endPage":"326","numberOfPages":"8","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":241589,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213917,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10980-011-9699-7"}],"volume":"27","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-12-28","publicationStatus":"PW","scienceBaseUri":"505a5053e4b0c8380cd6b5f1","contributors":{"authors":[{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":139586,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":436837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howard, Daniel M. 0000-0002-7563-7538 dhoward@usgs.gov","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":139585,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel M.","email":"dhoward@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":436836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":436838,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhang, Li","contributorId":98139,"corporation":false,"usgs":true,"family":"Zhang","given":"Li","affiliations":[],"preferred":false,"id":436839,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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