{"pageNumber":"1471","pageRowStart":"36750","pageSize":"25","recordCount":165309,"records":[{"id":70044100,"text":"70044100 - 2013 - Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example","interactions":[],"lastModifiedDate":"2013-02-26T17:59:42","indexId":"70044100","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","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":"Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example","docAbstract":"Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landscape Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10980-012-9830-4","usgsCitation":"Cross, P.C., Caillaud, D., and Heisey, D.M., 2013, Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example: Landscape Ecology, v. 28, no. 2, p. 247-257, https://doi.org/10.1007/s10980-012-9830-4.","productDescription":"11 p.","startPage":"247","endPage":"257","ipdsId":"IP-034645","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":268415,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10980-012-9830-4"},{"id":268416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-11-30","publicationStatus":"PW","scienceBaseUri":"53cd7a2ae4b0b2908510d4ed","contributors":{"authors":[{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":474810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caillaud, Damien","contributorId":31650,"corporation":false,"usgs":true,"family":"Caillaud","given":"Damien","email":"","affiliations":[],"preferred":false,"id":474811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heisey, Dennis M. dheisey@usgs.gov","contributorId":2455,"corporation":false,"usgs":true,"family":"Heisey","given":"Dennis","email":"dheisey@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":474809,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042646,"text":"70042646 - 2013 - Salmon-mediated nutrient flux in selected streams of the Columbia River basin, USA","interactions":[],"lastModifiedDate":"2013-04-20T19:45:03","indexId":"70042646","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Salmon-mediated nutrient flux in selected streams of the Columbia River basin, USA","docAbstract":"Salmon provide an important resource subsidy and linkage between marine and land-based ecosystems. This flow of energy and nutrients is not uni-directional (i.e., upstream only); in addition to passive nutrient export via stream flow, juvenile emigrants actively export nutrients from freshwater environments. In some cases, nutrient export can exceed import. We evaluated nutrient fluxes in streams across central Idaho, USA using Chinook salmon (Oncorhynchus tshawytscha) adult escapement and juvenile production data from 1998 to 2008. We found in the majority of stream-years evaluated, adults imported more nutrients than progeny exported; however, in 3% of the years, juveniles exported more nutrients than their parents imported. On average, juvenile emigrants exported 22 ± 3% of the nitrogen and 30 ± 4% of the phosphorus their parents imported. This relationship was density dependent and nonlinear; during periods of low adult abundance juveniles were larger and exported up to 194% and 268% of parental nitrogen and phosphorus inputs, respectively. We highlight minimum escapement thresholds that appear to 1) maintain consistently positive net nutrient flux and 2) reduce the average proportional rate of export across study streams. Our results suggest a state-shift occurs when adult spawner abundance falls below a threshold to a point where the probability of juvenile nutrient exports exceeding adult imports becomes increasingly likely.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Fisheries and Aquatic Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Canadian Science Publishing","publisherLocation":"Ottawa, Ontario","doi":"10.1139/cjfas-2012-0347","usgsCitation":"Kohler, A.E., Kusnierz, P.C., Copeland, T., Venditti, D.A., Denny, L., Gable, J., Lewis, B., Kinzer, R., Barnett, B., and Wipfli, M.S., 2013, Salmon-mediated nutrient flux in selected streams of the Columbia River basin, USA: Canadian Journal of Fisheries and Aquatic Sciences, v. 70, no. 3, p. 502-512, https://doi.org/10.1139/cjfas-2012-0347.","productDescription":"11 p.","startPage":"502","endPage":"512","ipdsId":"IP-039469","costCenters":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":268392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268391,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1139/cjfas-2012-0347"}],"country":"United States","state":"Idaho","otherGeospatial":"Columbia River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.46,42.15 ], [ -121.46,48.13 ], [ -111.19,48.13 ], [ -111.19,42.15 ], [ -121.46,42.15 ] ] ] } } ] }","volume":"70","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515ea0f6e4b088aa2258098c","contributors":{"authors":[{"text":"Kohler, Andre E.","contributorId":62491,"corporation":false,"usgs":true,"family":"Kohler","given":"Andre","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":471974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kusnierz, Paul C.","contributorId":13881,"corporation":false,"usgs":true,"family":"Kusnierz","given":"Paul","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":471970,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Copeland, Timothy","contributorId":27760,"corporation":false,"usgs":true,"family":"Copeland","given":"Timothy","email":"","affiliations":[],"preferred":false,"id":471971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Venditti, David A.","contributorId":38036,"corporation":false,"usgs":true,"family":"Venditti","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471972,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Denny, Lytle","contributorId":96172,"corporation":false,"usgs":true,"family":"Denny","given":"Lytle","email":"","affiliations":[],"preferred":false,"id":471977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gable, Josh","contributorId":7156,"corporation":false,"usgs":true,"family":"Gable","given":"Josh","email":"","affiliations":[],"preferred":false,"id":471969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lewis, Bert","contributorId":92138,"corporation":false,"usgs":true,"family":"Lewis","given":"Bert","email":"","affiliations":[],"preferred":false,"id":471976,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kinzer, Ryan","contributorId":45201,"corporation":false,"usgs":true,"family":"Kinzer","given":"Ryan","email":"","affiliations":[],"preferred":false,"id":471973,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barnett, Bruce","contributorId":82565,"corporation":false,"usgs":true,"family":"Barnett","given":"Bruce","email":"","affiliations":[],"preferred":false,"id":471975,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":471968,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70042510,"text":"70042510 - 2013 - A comment on \"Novel scavenger removal trials increase wind turbine-caused avian fatality estimates\"","interactions":[],"lastModifiedDate":"2018-03-29T15:16:16","indexId":"70042510","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","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":"A comment on \"Novel scavenger removal trials increase wind turbine-caused avian fatality estimates\"","docAbstract":"<p><span>In a recent paper, Smallwood et al. (2010) conducted a study to compare their “novel” approach to conducting carcass removal trials with what they term the “conventional” approach and to evaluate the effects of the different methods on estimated avian fatality at a wind power facility in California. A quick glance at Table 3 that succinctly summarizes their results and provides estimated fatality rates and 80% confidence intervals calculated using the 2 methods reveals a surprising result. The confidence intervals of all of their estimates and most of the conventional estimates extend below 0. These results imply that wind turbines may have the capacity to create live birds. But a more likely interpretation is that a serious error occurred in the calculation of either the average fatality rate or its standard error or both. Further evaluation of their methods reveals that the scientific basis for concluding that “many estimates of scavenger removal rates prior to [their] study were likely biased low due to scavenger swamping” and “previously reported estimates of avian fatality rates … should be adjusted upwards” was not evident in their analysis and results. Their comparison to conventional approaches was not applicable, their statistical models were questionable, and the conclusions they drew were unsupported.</span></p>","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/jwmg.468","usgsCitation":"Huso, M., and Erickson, W.P., 2013, A comment on \"Novel scavenger removal trials increase wind turbine-caused avian fatality estimates\": Journal of Wildlife Management, v. 77, no. 2, p. 213-215, https://doi.org/10.1002/jwmg.468.","productDescription":"3 p.","startPage":"213","endPage":"215","ipdsId":"IP-031078","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":268315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268311,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.468"}],"volume":"77","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-01-07","publicationStatus":"PW","scienceBaseUri":"539a2a60e4b0a59b2649726f","contributors":{"authors":[{"text":"Huso, Manuela M.P.","contributorId":80566,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela M.P.","affiliations":[],"preferred":false,"id":471670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erickson, Wallace P.","contributorId":78627,"corporation":false,"usgs":true,"family":"Erickson","given":"Wallace","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":471669,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043595,"text":"70043595 - 2013 - A data-based conservation planning tool for Florida panthers","interactions":[],"lastModifiedDate":"2013-03-04T21:06:08","indexId":"70043595","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1550,"text":"Environmental Modeling & Assessment","onlineIssn":" 1573-296","printIssn":"1420-2026","active":true,"publicationSubtype":{"id":10}},"title":"A data-based conservation planning tool for Florida panthers","docAbstract":"Habitat loss and fragmentation are the greatest threats to the endangered Florida panther (<i>Puma concolor coryi</i>). We developed a data-based habitat model and user-friendly interface so that land managers can objectively evaluate Florida panther habitat. We used a geographic information system (GIS) and the Mahalanobis distance statistic (<i>D</i><sup>2</sup>) to develop a model based on broad-scale landscape characteristics associated with panther home ranges. Variables in our model were Euclidean distance to natural land cover, road density, distance to major roads, human density, amount of natural land cover, amount of semi-natural land cover, amount of permanent or semi-permanent flooded area–open water, and a cost–distance variable. We then developed a Florida Panther Habitat Estimator tool, which automates and replicates the GIS processes used to apply the statistical habitat model. The estimator can be used by persons with moderate GIS skills to quantify effects of land-use changes on panther habitat at local and landscape scales. Example applications of the tool are presented.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modeling and Assessment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10666-012-9336-0","usgsCitation":"Murrow, J.L., Thatcher, C., van Manen, F., and Clark, J.D., 2013, A data-based conservation planning tool for Florida panthers: Environmental Modeling & Assessment, v. 18, no. 2, p. 159-170, https://doi.org/10.1007/s10666-012-9336-0.","productDescription":"12 p.","startPage":"159","endPage":"170","ipdsId":"IP-040629","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":268388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268382,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10666-012-9336-0"}],"country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.63,24.52 ], [ -87.63,31.0 ], [ -80.0,31.0 ], [ -80.0,24.52 ], [ -87.63,24.52 ] ] ] } } ] }","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-09-09","publicationStatus":"PW","scienceBaseUri":"5135d072e4b03b8ec4025b38","contributors":{"authors":[{"text":"Murrow, Jennifer L.","contributorId":92945,"corporation":false,"usgs":true,"family":"Murrow","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":473934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thatcher, Cindy A.","contributorId":79604,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy A.","affiliations":[],"preferred":false,"id":473933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Manen, Frank T.","contributorId":51172,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank T.","affiliations":[],"preferred":false,"id":473932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":473931,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043719,"text":"70043719 - 2013 - A comprehensive change detection method for updating the National Land Cover Database to circa 2011","interactions":[],"lastModifiedDate":"2013-02-26T12:57:26","indexId":"70043719","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","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":"A comprehensive change detection method for updating the National Land Cover Database to circa 2011","docAbstract":"The importance of characterizing, quantifying, and monitoring land cover, land use, and their changes has been widely recognized by global and environmental change studies. Since the early 1990s, three U.S. National Land Cover Database (NLCD) products (circa 1992, 2001, and 2006) have been released as free downloads for users. The NLCD 2006 also provides land cover change products between 2001 and 2006. To continue providing updated national land cover and change datasets, a new initiative in developing NLCD 2011 is currently underway. We present a new Comprehensive Change Detection Method (CCDM) designed as a key component for the development of NLCD 2011 and the research results from two exemplar studies. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (CV, RCVMAX, dNBR, and dNDVI) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. For NLCD 2011, the improved and enhanced change products obtained from the CCDM provide critical information on location, magnitude, and direction of potential change areas and serve as a basis for further characterizing land cover changes for the nation. An accuracy assessment from the two study areas show 100% agreement between CCDM mapped no-change class with reference dataset, and 18% and 82% disagreement for the change class for WRS path/row p22r39 and p33r33, respectively. The strength of the CCDM is that the method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and anthropogenic disturbances potentially associated with land cover changes on different landscapes.","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.2013.01.012","usgsCitation":"Jin, S., Yang, L., Danielson, P., Homer, C.G., Fry, J., and Xian, G., 2013, A comprehensive change detection method for updating the National Land Cover Database to circa 2011: Remote Sensing of Environment, v. 132, p. 159-175, https://doi.org/10.1016/j.rse.2013.01.012.","productDescription":"17 p.","startPage":"159","endPage":"175","ipdsId":"IP-041925","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":268381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268380,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2013.01.012"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","volume":"132","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd49a9e4b0b290850ef516","chorus":{"doi":"10.1016/j.rse.2013.01.012","url":"http://dx.doi.org/10.1016/j.rse.2013.01.012","publisher":"Elsevier BV","authors":"Jin Suming, Yang Limin, Danielson Patrick, Homer Collin, Fry Joyce, Xian George","journalName":"Remote Sensing of Environment","publicationDate":"5/2013","auditedOn":"4/22/2016"},"contributors":{"authors":[{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@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":474161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":474160,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Patrick 0000-0002-2990-2783 pdanielson@usgs.gov","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":3551,"corporation":false,"usgs":true,"family":"Danielson","given":"Patrick","email":"pdanielson@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":474159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","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":474157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fry, Joyce 0000-0002-8466-9582 jfry@usgs.gov","orcid":"https://orcid.org/0000-0002-8466-9582","contributorId":3147,"corporation":false,"usgs":true,"family":"Fry","given":"Joyce","email":"jfry@usgs.gov","affiliations":[],"preferred":true,"id":474158,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xian, George 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":76589,"corporation":false,"usgs":true,"family":"Xian","given":"George","affiliations":[],"preferred":false,"id":474162,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70188865,"text":"70188865 - 2013 -  Correlation of geothermal springs with sub-surface fault terminations revealed by high-resolution, UAV-acquired magnetic data","interactions":[],"lastModifiedDate":"2017-06-27T14:49:17","indexId":"70188865","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":" Correlation of geothermal springs with sub-surface fault terminations revealed by high-resolution, UAV-acquired magnetic data","docAbstract":"<p><span>There is widespread agreement that geothermal springs in extensional geothermal systems are concentrated at fault tips and in fault interaction zones where porosity and permeability are dynamically maintained (Curewitz and Karson, 1997; Faulds et al., 2010). Making these spatial correlations typically involves geological and geophysical studies in order to map structures and their relationship to springs at the surface. Geophysical studies include gravity and magnetic surveys, which are useful for identifying buried, intra-basin structures, especially in areas where highly magnetic, dense mafic volcanic rocks are interbedded with, and faulted against less magnetic, less dense sedimentary rock. High-resolution magnetic data can also be collected from the air in order to provide continuous coverage. Unmanned aerial systems (UAS) are well-suited for conducting these surveys as they can provide uniform, low-altitude, high-resolution coverage of an area without endangering crew. In addition, they are more easily adaptable to changes in flight plans as data are collected, and improve efficiency. We have developed and tested a new system to collect magnetic data using small-platform UAS. We deployed this new system in Surprise Valley, CA, in September, 2012, on NASA's SIERRA UAS to perform a reconnaissance survey of the entire valley as well as detailed surveys in key transition zones. This survey has enabled us to trace magnetic anomalies seen in ground-based profiles along their length. Most prominent of these is an intra-basin magnetic high that we interpret as a buried, faulted mafic dike that runs a significant length of the valley. Though this feature lacks surface expression, it appears to control the location of geothermal springs. All of the major hot springs on the east side of the valley lie along the edge of the high, and more specifically, at structural transitions where the high undergoes steps, bends, or breaks. The close relationship between the springs and structure terminations revealed by this study is unprecedented. Collecting magnetic data via UAS represents a new capability in geothermal exploration of remote and dangerous areas that significantly enhances our ability to map the subsurface.</span></p>","largerWorkTitle":"Proceedings Thirty-eighth Workshop on Geothermal Reservoir Engineering","conferenceTitle":"Thirty-Eighth Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 11-13, 2013","conferenceLocation":"Stanford University, Stanford, California","language":"English","usgsCitation":"Glen, J.M., A.E. Egger, C. Ippolito, and , N., 2013,  Correlation of geothermal springs with sub-surface fault terminations revealed by high-resolution, UAV-acquired magnetic data, <i>in</i> Proceedings Thirty-eighth Workshop on Geothermal Reservoir Engineering, Stanford University, Stanford, California, February 11-13, 2013, 8 p. .","productDescription":"8 p. ","ipdsId":"IP-044179","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":343009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343008,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcommons.cwu.edu/geological_sciences/2/"}],"country":"United States","state":"California","county":"Modoc County ","otherGeospatial":"Surprise Valley ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.10528564453125,\n              41.92271616673922\n            ],\n            [\n              -120.14648437499999,\n              41.864447405239375\n            ],\n            [\n              -120.18356323242188,\n              41.78769700539063\n            ],\n            [\n              -120.20278930664062,\n              41.70982942509964\n            ],\n            [\n              -120.21514892578125,\n              41.66162721430806\n            ],\n            [\n              -120.19454956054686,\n              41.59182393372352\n            ],\n            [\n              -120.17807006835936,\n              41.549700145132725\n            ],\n            [\n              -120.18905639648438,\n              41.49932105451145\n            ],\n            [\n              -120.1519775390625,\n              41.43860847395721\n            ],\n            [\n              -120.12451171875,\n              41.35104125623227\n            ],\n            [\n              -120.10253906249999,\n              41.29122180718259\n            ],\n            [\n              -120.03799438476561,\n              41.1724519493126\n            ],\n            [\n              -120.00503540039061,\n              41.176586696571015\n            ],\n            [\n              -120.0146484375,\n              41.27058168052551\n            ],\n            [\n              -120.01190185546875,\n              41.307729208348015\n            ],\n            [\n              -120.01327514648438,\n              41.38608229923676\n            ],\n            [\n              -120.00778198242186,\n              41.54764462357737\n            ],\n            [\n              -120.02975463867188,\n              41.790768787851285\n            ],\n            [\n              -120.00228881835938,\n              41.92782492551717\n            ],\n            [\n              -120.02014160156249,\n              41.96051129429777\n            ],\n            [\n              -120.10528564453125,\n              41.92271616673922\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536eaee4b062508e3c7ab5","contributors":{"authors":[{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"A.E. Egger","contributorId":193534,"corporation":false,"usgs":false,"family":"A.E. Egger","affiliations":[],"preferred":false,"id":700742,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"C. Ippolito","contributorId":193535,"corporation":false,"usgs":false,"family":"C. Ippolito","affiliations":[],"preferred":false,"id":700743,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":" N.Athens","contributorId":193536,"corporation":false,"usgs":false,"given":"N.Athens","email":"","affiliations":[],"preferred":false,"id":700744,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70057429,"text":"ofr20131202B - 2013 - Hyperspectral surface materials map of quadrangle 3562, Khawja-Jir (403) and Murghab (404) quadrangles, Afghanistan, showing iron-bearing minerals and other materials","interactions":[],"lastModifiedDate":"2014-03-10T10:09:31","indexId":"ofr20131202B","displayToPublicDate":"2013-02-25T12:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1202","chapter":"B","title":"Hyperspectral surface materials map of quadrangle 3562, Khawja-Jir (403) and Murghab (404) quadrangles, Afghanistan, showing iron-bearing minerals and other materials","docAbstract":"<p>This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan.</p>\n<br/>\n<p>Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines.</p>\n<br/>\n<p>The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131202B","collaboration":"Prepared in cooperation with the U.S. Geological Survey under the auspices of the U.S. Department of Defense Task Force for Business and Stability Operations","usgsCitation":"King, T., Hoefen, T.M., Kokaly, R., Livo, K.E., Johnson, M., and Giles, S.A., 2013, Hyperspectral surface materials map of quadrangle 3562, Khawja-Jir (403) and Murghab (404) quadrangles, Afghanistan, showing iron-bearing minerals and other materials: U.S. Geological Survey Open-File Report 2013-1202, 37 x 23 inches, https://doi.org/10.3133/ofr20131202B.","productDescription":"37 x 23 inches","onlineOnly":"Y","ipdsId":"IP-050472","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":282356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131202b.jpg"},{"id":283578,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1202/B/"},{"id":283579,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1202/B/pdf/ofr2013-1202b.pdf"}],"scale":"250000","projection":"Universal Transverse Mercator","datum":"WGS 1984","country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 62.0,35.0 ], [ 62.0,36.0 ], [ 64.0,36.0 ], [ 64.0,35.0 ], [ 62.0,35.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd61dae4b0b290850fdc9e","contributors":{"authors":[{"text":"King, Trude","contributorId":29831,"corporation":false,"usgs":true,"family":"King","given":"Trude","email":"","affiliations":[],"preferred":false,"id":486684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":486680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":81442,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","affiliations":[],"preferred":false,"id":486685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Livo, Keith E. 0000-0001-7331-8130 elivo@usgs.gov","orcid":"https://orcid.org/0000-0001-7331-8130","contributorId":1750,"corporation":false,"usgs":true,"family":"Livo","given":"Keith","email":"elivo@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":486683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Michaela R. 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":1013,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela R.","email":"mrjohns@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":486681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Giles, Stuart A. 0000-0002-8696-5078 sgiles@usgs.gov","orcid":"https://orcid.org/0000-0002-8696-5078","contributorId":1233,"corporation":false,"usgs":true,"family":"Giles","given":"Stuart","email":"sgiles@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":486682,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70146651,"text":"70146651 - 2013 - Fens as whole-ecosystem gauges of groundwater recharge under climate change","interactions":[],"lastModifiedDate":"2015-04-20T09:17:35","indexId":"70146651","displayToPublicDate":"2013-02-25T10:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Fens as whole-ecosystem gauges of groundwater recharge under climate change","docAbstract":"<p>Currently, little is known about the impact of climate change on groundwater recharge in the Sierra Nevada and southern Cascade Range of California or other mountainous regions of the world. The purpose of this study was to determine whether small alpine peat lands called fens can be used as whole-ecosystem gauges of groundwater recharge through time. Fens are sustained by groundwater discharge and are highly sensitive to changes in groundwater flow due to hydrologic disturbance including climate change. Seven fens in the Sierra Nevada and southern Cascade Range were studied over a 50-80 year period using historic aerial photography. In each aerial photograph, fen areas were identified as open lawn and partially treed areas that exhibited (1) dark brownish-green coloring or various shades of gray and black in black and white imagery and (2) mottling of colors and clustering of vegetation, which signified a distinct moss canopy with overlying clumped sedge vegetation. In addition to the aerial photography study, a climate analysis for the study sites was carried out using both measured data (U.S. Department of Agriculture Natural Resources Conservation Service SNOwpack TELemetry system) and modeled data (a downscaled version of the Parameter-elevation Regressions on Independent Slopes Model) for the period from 1951 to 2010. Over the study period, the five fens in the Sierra Nevada were found to be decreasing between 10% and 16% in delineated area. The climate analysis revealed significant increases through time in annual mean minimum temperature (T<sub>min</sub>) between 1951-1980 and 1981-2010. In addition, April 1 snow water equivalent and snowpack longevity also decreased between 1951-1980 and 1981-2010. For the fens in the Cascade Range, there were no discernible changes in delineated area. At these sites, increases in T<sub>min</sub> occurred only within the past 20-25 years and decreases in snowpack longevity were more subtle. A conceptual model is presented, which illustrates that basic differences in hydrogeology of the Sierra Nevada vs. the Cascade Range may control the threshold at which changes in delineated fen areas are discernible. Overall, the results from this study show that fens in the Sierra Nevada have strong potential as whole ecosystem gauges for determining long-term changes in groundwater recharge under climate change. Due to either more moderate climate change and/or hydrogeological differences, fens in the southern Cascade Range currently do not appear to have the same utility. A greater sample size of fens in the Sierra Nevada is needed to confirm the general applicability of this method. In addition, future work needs to focus on integrating fen monitoring with geochemical and/or isotopic process-level studies in order to quantify changes in groundwater recharge identified using this new approach.</p>","language":"English","publisher":"European Geophysical Society","publisherLocation":"New York, NY","doi":"10.1016/j.jhydrol.2012.11.056","usgsCitation":"Drexler, J., Knifong, D.L., Tuil, J., Flint, L.E., and Flint, A.L., 2013, Fens as whole-ecosystem gauges of groundwater recharge under climate change: Journal of Hydrology, v. 481, p. 22-34, https://doi.org/10.1016/j.jhydrol.2012.11.056.","productDescription":"13 p.","startPage":"22","endPage":"34","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040704","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":299768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"481","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5536233ae4b0b22a15807a94","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":1659,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith Z.","email":"jdrexler@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":545228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knifong, Donna L. dknifong@usgs.gov","contributorId":1517,"corporation":false,"usgs":true,"family":"Knifong","given":"Donna","email":"dknifong@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":545227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tuil, JayLee","contributorId":140341,"corporation":false,"usgs":false,"family":"Tuil","given":"JayLee","email":"","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":545230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545226,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70044000,"text":"70044000 - 2013 - Nitrate in watersheds: straight from soils to streams?","interactions":[],"lastModifiedDate":"2013-04-20T19:35:59","indexId":"70044000","displayToPublicDate":"2013-02-25T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Nitrate in watersheds: straight from soils to streams?","docAbstract":"Human activities are rapidly increasing the global supply of reactive N and substantially altering the structure and hydrologic connectivity of managed ecosystems. There is long-standing recognition that N must be removed along hydrologic flowpaths from uplands to streams, yet it has proven difficult to assess the generality of this removal across ecosystem types, and whether these patterns are influenced by land-use change. To assess how well upland nitrate (NO<sub>3</sub><sup>-</sup>) loss is reflected in stream export, we gathered information from >50 watershed biogeochemical studies that reported nitrate concentrations ([NO<sub>3</sub><sup>-</sup>]) for stream water and for either upslope soil solution or groundwater NO<sub>3</sub><sup>-</sup> to examine whether stream export of NO3- accurately reflects upland NO<sub>3</sub><sup>-</sup> losses. In this dataset, soil solution and streamwater [NO<sub>3</sub><sup>-</sup>] were correlated across 40 undisturbed forest watersheds, with streamwater [NO<sub>3</sub><sup>-</sup>] typically half (median = 50%) soil solution [NO<sub>3</sub><sup>-</sup>]. A similar relationship was seen in 10 disturbed forest watersheds. However, for 12 watersheds with significant agricultural or urban development, the intercept and slope were both significantly higher than the relationship seen in forest watersheds. Differences in concentration between soil solution or groundwater and stream water may be attributed to biological uptake, microbial processes including denitrification, and/or preferential flow routing. The results of this synthesis are consistent with the hypotheses that undisturbed watersheds have a significant capacity to remove nitrate after it passes below the rooting zone and that land use changes tend to alter the efficiency or the length of watershed flowpaths, leading to reductions in nitrate removal and increased stream nitrate concentrations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research G: Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","publisherLocation":"Washington, D.C.","doi":"10.1002/jgrg.20030","usgsCitation":"Sudduth, E.B., Perakis, S., and Bernhardt, E., 2013, Nitrate in watersheds: straight from soils to streams?: Journal of Geophysical Research G: Biogeosciences, v. 118, no. G1, p. 291-302, https://doi.org/10.1002/jgrg.20030.","productDescription":"45 p.","startPage":"291","endPage":"302","ipdsId":"IP-018046","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":268260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268256,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrg.20030"}],"volume":"118","issue":"G1","noUsgsAuthors":false,"publicationDate":"2013-03-21","publicationStatus":"PW","scienceBaseUri":"512c87e9e4b0855fde669730","contributors":{"authors":[{"text":"Sudduth, Elizabeth B.","contributorId":8747,"corporation":false,"usgs":true,"family":"Sudduth","given":"Elizabeth","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":474588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perakis, Steven S. 0000-0003-0703-9314","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":16797,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven S.","affiliations":[],"preferred":false,"id":474589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bernhardt, Emily S.","contributorId":92143,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily S.","affiliations":[{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false}],"preferred":false,"id":474590,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043953,"text":"70043953 - 2013 - An ecohydraulic model to identify and monitor moapa dace habitat","interactions":[],"lastModifiedDate":"2013-02-25T10:27:58","indexId":"70043953","displayToPublicDate":"2013-02-25T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"An ecohydraulic model to identify and monitor moapa dace habitat","docAbstract":"Moapa dace (<i>Moapa coriacea</i>) is a critically endangered thermophilic minnow native to the Muddy River ecosystem in southeastern Nevada, USA. Restricted to temperatures between 26.0 and 32.0°C, these fish are constrained to the upper two km of the Muddy River and several small tributaries fed by warm springs. Habitat alterations, nonnative species invasion, and water withdrawals during the 20th century resulted in a drastic decline in the dace population and in 1979 the Moapa Valley National Wildlife Refuge (Refuge) was created to protect them. The goal of our study was to determine the potential effects of reduced surface flows that might result from groundwater pumping or water diversions on Moapa dace habitat inside the Refuge. We accomplished our goal in several steps. First, we conducted snorkel surveys to determine the locations of Moapa dace on three warm-spring tributaries of the Muddy River. Second, we conducted hydraulic simulations over a range of flows with a two-dimensional hydrodynamic model. Third, we developed a set of Moapa dace habitat models with logistic regression and a geographic information system. Fourth, we estimated Moapa dace habitat over a range of flows (plus or minus 30% of base flow). Our spatially explicit habitat models achieved classification accuracies between 85% and 91%, depending on the snorkel survey and creek. Water depth was the most significant covariate in our models, followed by substrate, Froude number, velocity, and water temperature. Hydraulic simulations showed 2-11% gains in dace habitat when flows were increased by 30%, and 8-32% losses when flows were reduced by 30%. To ensure the health and survival of Moapa dace and the Muddy River ecosystem, groundwater and surface-water withdrawals and diversions need to be carefully monitored, while fully implementing a proactive conservation strategy.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PLoS","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0055551","usgsCitation":"Hatten, J.R., Batt, T.R., Scoppettone, G.G., and Dixon, C.J., 2013, An ecohydraulic model to identify and monitor moapa dace habitat: PLoS ONE, v. 8, no. 2, 12 p., https://doi.org/10.1371/journal.pone.0055551.","productDescription":"12 p.","numberOfPages":"12","ipdsId":"IP-040200","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":473945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0055551","text":"Publisher Index Page"},{"id":268203,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0055551"},{"id":268204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.720236063,36.7088462532 ], [ -114.720236063,36.7149528124 ], [ -114.7083055973,36.7149528124 ], [ -114.7083055973,36.7088462532 ], [ -114.720236063,36.7088462532 ] ] ] } } ] }","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-02-07","publicationStatus":"PW","scienceBaseUri":"512c87e7e4b0855fde66972c","contributors":{"authors":[{"text":"Hatten, James R. 0000-0003-4676-8093 jhatten@usgs.gov","orcid":"https://orcid.org/0000-0003-4676-8093","contributorId":3431,"corporation":false,"usgs":true,"family":"Hatten","given":"James","email":"jhatten@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Batt, Thomas R. tbatt@usgs.gov","contributorId":3432,"corporation":false,"usgs":true,"family":"Batt","given":"Thomas","email":"tbatt@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scoppettone, Gayton G. gary_scoppettone@usgs.gov","contributorId":2848,"corporation":false,"usgs":true,"family":"Scoppettone","given":"Gayton","email":"gary_scoppettone@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dixon, Christopher J.","contributorId":42110,"corporation":false,"usgs":true,"family":"Dixon","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":474540,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043969,"text":"70043969 - 2013 - Adjusting survival estimates for premature transmitter failure: A case study from the Sacramento-San Joaquin Delta","interactions":[],"lastModifiedDate":"2016-05-04T15:45:36","indexId":"70043969","displayToPublicDate":"2013-02-25T00:00:00","publicationYear":"2013","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":"Adjusting survival estimates for premature transmitter failure: A case study from the Sacramento-San Joaquin Delta","docAbstract":"<p>In telemetry studies, premature tag failure causes negative bias in fish survival estimates because tag failure is interpreted as fish mortality. We used mark-recapture modeling to adjust estimates of fish survival for a previous study where premature tag failure was documented. High rates of tag failure occurred during the Vernalis Adaptive Management Plan&rsquo;s (VAMP) 2008 study to estimate survival of fall-run Chinook salmon (<i class=\"EmphasisTypeItalic \">Oncorhynchus tshawytscha</i>) during migration through the San Joaquin River and Sacramento-San Joaquin Delta, California. Due to a high rate of tag failure, the observed travel time distribution was likely negatively biased, resulting in an underestimate of tag survival probability in this study. Consequently, the bias-adjustment method resulted in only a small increase in estimated fish survival when the observed travel time distribution was used to estimate the probability of tag survival. Since the bias-adjustment failed to remove bias, we used historical travel time data and conducted a sensitivity analysis to examine how fish survival might have varied across a range of tag survival probabilities. Our analysis suggested that fish survival estimates were low (95% confidence bounds range from 0.052 to 0.227) over a wide range of plausible tag survival probabilities (0.48&ndash;1.00), and this finding is consistent with other studies in this system. When tags fail at a high rate, available methods to adjust for the bias may perform poorly. Our example highlights the importance of evaluating the tag life assumption during survival studies, and presents a simple framework for evaluating adjusted survival estimates when auxiliary travel time data are available.</p>","language":"English","publisher":"Kluwer Academic Publishers","doi":"10.1007/s10641-012-0016-3","usgsCitation":"Holbrook, C., Perry, R.W., Brandes, P., and Adams, N.S., 2013, Adjusting survival estimates for premature transmitter failure: A case study from the Sacramento-San Joaquin Delta: Environmental Biology of Fishes, v. 96, no. 2, p. 165-173, https://doi.org/10.1007/s10641-012-0016-3.","productDescription":"9 p.","startPage":"165","endPage":"173","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-027244","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":268202,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta, San Joaquin River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.929093,37.735197 ], [ -121.929093,38.126074 ], [ -121.300766,38.126074 ], [ -121.300766,37.735197 ], [ -121.929093,37.735197 ] ] ] } } ] }","volume":"96","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-04-26","publicationStatus":"PW","scienceBaseUri":"512c87dfe4b0855fde669728","contributors":{"authors":[{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":4198,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher M.","email":"cholbrook@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":474561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandes, Patricia L.","contributorId":25834,"corporation":false,"usgs":true,"family":"Brandes","given":"Patricia L.","affiliations":[],"preferred":false,"id":474562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474560,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70044020,"text":"ofr20131034 - 2013 - Water quality in the Anacostia River, Maryland and Rock Creek, Washington, D.C.: Continuous and discrete monitoring with simulations to estimate concentrations and yields of nutrients, suspended sediment, and bacteria","interactions":[],"lastModifiedDate":"2023-03-09T20:14:16.958533","indexId":"ofr20131034","displayToPublicDate":"2013-02-25T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1034","title":"Water quality in the Anacostia River, Maryland and Rock Creek, Washington, D.C.: Continuous and discrete monitoring with simulations to estimate concentrations and yields of nutrients, suspended sediment, and bacteria","docAbstract":"Concentrations and loading estimates for nutrients, suspended sediment, and <i>E. coli</i> bacteria were summarized for three water-quality monitoring stations on the Anacostia River in Maryland and one station on Rock Creek in Washington, D.C. Both streams are tributaries to the Potomac River in the Washington, D.C. metropolitan area and contribute to the Chesapeake Bay estuary. Two stations on the Anacostia River, Northeast Branch at Riverdale, Maryland and Northwest Branch near Hyattsville, Maryland, have been monitored for water quality during the study period from 2003 to 2011 and are located near the shift from nontidal to tidal conditions near Bladensburg, Maryland. A station on Paint Branch is nested above the station on the Northeast Branch Anacostia River, and has slightly less developed land cover than the Northeast and Northwest Branch stations. The Rock Creek station is located in Rock Creek Park, but the land cover in the watershed surrounding the park is urbanized. Stepwise log-linear regression models were developed to estimate the concentrations of suspended sediment, total nitrogen, total phosphorus, and <i>E. coli</i> bacteria from continuous field monitors. Turbidity was the strongest predictor variable for all water-quality parameters. For bacteria, water temperature improved the models enough to be included as a second predictor variable due to the strong dependence of stream metabolism on temperature. Coefficients of determination (R<sup>2</sup>) for the models were highest for log concentrations of suspended sediment (0.9) and total phosphorus (0.8 to 0.9), followed by <i>E. coli</i> bacteria (0.75 to 0.8), and total nitrogen (0.6). Water-quality data provided baselines for conditions prior to accelerated implementation of multiple stormwater controls in the watersheds. Counties are currently in the process of enhancing stormwater controls in both watersheds. Annual yields were estimated for suspended sediment, total nitrogen, total phosphorus, and <i>E. coli</i> bacteria using the U.S. Geological Survey model LOADEST with hourly time steps of turbidity, flow, and time. Yields of all four parameters were within ranges found in other urbanized watersheds in Chesapeake Bay. Annual yields for all four watersheds over the period of study were estimated for suspended sediment (65,500 – 166,000 kilograms per year per square kilometer; kg/yr/km<sup>2</sup>), total nitrogen (465 - 911 kg/yr/km<sup>2</sup>), total phosphorus (36 - 113 kg/yr/km<sup>2</sup>), and <i>E. coli</i> bacteria (6.0 – 38 x 10<sup>12</sup> colony forming units/yr/km<sup>2</sup>). The length of record was not sufficient to determine trends for any of the water-quality parameters; within confidence intervals of the models, results were similar to loads determined by previous studies for the Northeast and Northwest Branch stations of the Anacostia River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131034","collaboration":"Prepared in cooperation with Montgomery County, Maryland","usgsCitation":"Miller, C.V., Chanat, J.G., and Bell, J.M., 2013, Water quality in the Anacostia River, Maryland and Rock Creek, Washington, D.C.: Continuous and discrete monitoring with simulations to estimate concentrations and yields of nutrients, suspended sediment, and bacteria: U.S. Geological Survey Open-File Report 2013-1034, vi, 37 p., https://doi.org/10.3133/ofr20131034.","productDescription":"vi, 37 p.","startPage":"i","endPage":"37","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":268259,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1034.gif"},{"id":268257,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1034/"},{"id":268258,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1034/pdf/ofr2013-1034.pdf"}],"country":"United States","state":"Maryl","city":"Washington;D.C.","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.49,37.89 ], [ -79.49,39.72 ], [ -75.05,39.72 ], [ -75.05,37.89 ], [ -79.49,37.89 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512c87eae4b0855fde669734","contributors":{"authors":[{"text":"Miller, Cherie V. 0000-0001-7765-5919 cvmiller@usgs.gov","orcid":"https://orcid.org/0000-0001-7765-5919","contributorId":863,"corporation":false,"usgs":true,"family":"Miller","given":"Cherie","email":"cvmiller@usgs.gov","middleInitial":"V.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":474638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chanat, Jeffrey G. 0000-0002-3629-7307 jchanat@usgs.gov","orcid":"https://orcid.org/0000-0002-3629-7307","contributorId":5062,"corporation":false,"usgs":true,"family":"Chanat","given":"Jeffrey","email":"jchanat@usgs.gov","middleInitial":"G.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Joseph M. 0000-0002-2536-2070 jmbell@usgs.gov","orcid":"https://orcid.org/0000-0002-2536-2070","contributorId":5063,"corporation":false,"usgs":true,"family":"Bell","given":"Joseph","email":"jmbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474640,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70155066,"text":"70155066 - 2013 - Site preparation for switchgrass intercropping in loblolly pine plantations reduces retained trees and snags, but maintains downed woody debris","interactions":[],"lastModifiedDate":"2015-09-16T09:07:52","indexId":"70155066","displayToPublicDate":"2013-02-23T01:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3886,"text":"Forestry","active":true,"publicationSubtype":{"id":10}},"title":"Site preparation for switchgrass intercropping in loblolly pine plantations reduces retained trees and snags, but maintains downed woody debris","docAbstract":"<p>Within young pine (<i>Pinus</i> spp.) plantations, coarse woody debris (CWD) and green trees are important habitat structures that may be impacted by the production of biofuel feedstock. Therefore, we compared site preparation procedures associated with switchgrass (<i>Panicum virgatum</i> L.) intercropping to determine effects on CWD and green trees in stands (<i>n</i> = 24) site-prepared for intercropping, with switchgrass only, or pine plantation in Mississippi, USA. Following site preparation, CWD dispersal or volume did not differ between intercropped and control stands. Intercropped stands had significantly fewer retained trees and snags. Switchgrass monocultures had no retained trees or piles and significantly fewer pieces and less volume of CWD than the other treatments. Our results suggest switchgrass intercropping may provide similar habitat quality to traditional pine plantations for wildlife species using these areas in the year following disturbance, but may provide a less suitable habitat for species that require snags. However, the relationship between snag reduction and wildlife population response in an intercropped setting is not clear and should be further investigated. Regardless, if retaining snags is a desired outcome, site preparation for switchgrass should be restricted to the interbed area where it will be cultivated as opposed to extensive debris removal from the entire site. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</p>","language":"English","publisher":"Oxford University Press","doi":"10.1093/forestry/cpt004","usgsCitation":"Loman, Z., Riffell, S.K., Miller, D.A., Martin, J.A., and Vilella, F., 2013, Site preparation for switchgrass intercropping in loblolly pine plantations reduces retained trees and snags, but maintains downed woody debris: Forestry, v. 86, no. 3, p. 353-360, https://doi.org/10.1093/forestry/cpt004.","productDescription":"8 p.","startPage":"353","endPage":"360","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040504","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473946,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/forestry/cpt004","text":"Publisher Index Page"},{"id":308147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","county":"Kemper County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.3461,32.9278],[-88.3559,32.8499],[-88.3727,32.7042],[-88.3883,32.5778],[-88.5413,32.5771],[-88.5538,32.5772],[-88.7878,32.5763],[-88.8014,32.576],[-88.8134,32.5761],[-88.8167,32.5762],[-88.9135,32.5753],[-88.9161,32.8272],[-88.9158,32.8463],[-88.9169,32.9228],[-88.8131,32.9241],[-88.5676,32.9263],[-88.3461,32.9278]]]},\"properties\":{\"name\":\"Kemper\",\"state\":\"MS\"}}]}","volume":"86","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-02-20","publicationStatus":"PW","scienceBaseUri":"55fa92d3e4b05d6c4e501ad1","contributors":{"authors":[{"text":"Loman, Zachary G.","contributorId":145932,"corporation":false,"usgs":false,"family":"Loman","given":"Zachary G.","affiliations":[],"preferred":false,"id":568495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riffell, Samuel K.","contributorId":102386,"corporation":false,"usgs":true,"family":"Riffell","given":"Samuel","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":568496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Darrin A. damiller@usgs.gov","contributorId":4356,"corporation":false,"usgs":true,"family":"Miller","given":"Darrin","email":"damiller@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":568497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, James A.","contributorId":145934,"corporation":false,"usgs":false,"family":"Martin","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":568498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vilella, Francisco fvilella@usgs.gov","contributorId":4255,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":564761,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70043889,"text":"ofr20131023 - 2013 - A conceptual prototype for the next-generation national elevation dataset","interactions":[],"lastModifiedDate":"2017-05-16T16:13:06","indexId":"ofr20131023","displayToPublicDate":"2013-02-22T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1023","title":"A conceptual prototype for the next-generation national elevation dataset","docAbstract":"In 2012 the U.S. Geological Survey's (USGS) National Geospatial Program (NGP) funded a study to develop a conceptual prototype for a new National Elevation Dataset (NED) design with expanded capabilities to generate and deliver a suite of bare earth and above ground feature information over the United States. This report details the research on identifying operational requirements based on prior research, evaluation of what is needed for the USGS to meet these requirements, and development of a possible conceptual framework that could potentially deliver the kinds of information that are needed to support NGP's partners and constituents. This report provides an initial proof-of-concept demonstration using an existing dataset, and recommendations for the future, to inform NGP's ongoing and future elevation program planning and management decisions. The demonstration shows that this type of functional process can robustly create derivatives from lidar point cloud data; however, more research needs to be done to see how well it extends to multiple datasets.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131023","usgsCitation":"Stoker, J.M., Heidemann, H.K., Evans, G.A., and Greenlee, S.K., 2013, A conceptual prototype for the next-generation national elevation dataset: U.S. Geological Survey Open-File Report 2013-1023, 52 p., https://doi.org/10.3133/ofr20131023.","productDescription":"52 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-042370","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":267933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1023.gif"},{"id":267931,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1023/"},{"id":267932,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1023/ofr13-1023.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173.0,16.916 ], [ 173.0,71.833 ], [ -66.95,71.833 ], [ -66.95,16.916 ], [ 173.0,16.916 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5128935fe4b01b9ee8b50c4b","contributors":{"authors":[{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":474398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heidemann, Hans Karl 0000-0003-4306-359X","orcid":"https://orcid.org/0000-0003-4306-359X","contributorId":30085,"corporation":false,"usgs":true,"family":"Heidemann","given":"Hans","email":"","middleInitial":"Karl","affiliations":[],"preferred":false,"id":474397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evans, Gayla A. 0000-0001-5072-4232 gevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-4232","contributorId":3125,"corporation":false,"usgs":true,"family":"Evans","given":"Gayla","email":"gevans@usgs.gov","middleInitial":"A.","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":474395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greenlee, Susan K. sgreenlee@usgs.gov","contributorId":3326,"corporation":false,"usgs":true,"family":"Greenlee","given":"Susan","email":"sgreenlee@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":474396,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043868,"text":"sir20125222 - 2013 - Community exposure to tsunami hazards in California","interactions":[],"lastModifiedDate":"2013-02-21T16:02:43","indexId":"sir20125222","displayToPublicDate":"2013-02-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5222","title":"Community exposure to tsunami hazards in California","docAbstract":"Evidence of past events and modeling of potential events suggest that tsunamis are significant threats to low-lying communities on the California coast. To reduce potential impacts of future tsunamis, officials need to understand how communities are vulnerable to tsunamis and where targeted outreach, preparedness, and mitigation efforts may be warranted. Although a maximum tsunami-inundation zone based on multiple sources has been developed for the California coast, the populations and businesses in this zone have not been documented in a comprehensive way. To support tsunami preparedness and risk-reduction planning in California, this study documents the variations among coastal communities in the amounts, types, and percentages of developed land, human populations, and businesses in the maximum tsunami-inundation zone. The tsunami-inundation zone includes land in 94 incorporated cities, 83 unincorporated communities, and 20 counties on the California coast. According to 2010 U.S. Census Bureau data, this tsunami-inundation zone contains 267,347 residents (1 percent of the 20-county resident population), of which 13 percent identify themselves as Hispanic or Latino, 14 percent identify themselves as Asian, 16 percent are more than 65 years in age, 12 percent live in unincorporated areas, and 51 percent of the households are renter occupied. Demographic attributes related to age, race, ethnicity, and household status of residents in tsunami-prone areas demonstrate substantial range among communities that exceed these regional averages. The tsunami-inundation zone in several communities also has high numbers of residents in institutionalized and noninstitutionalized group quarters (for example, correctional facilities and military housing, respectively). Communities with relatively high values in the various demographic categories are identified throughout the report. The tsunami-inundation zone contains significant nonresidential populations based on 2011 economic data from Infogroup (2011), including 168,565 employees (2 percent of the 20-county labor force) at 15,335 businesses that generate approximately $30 billion in annual sales. Although the regional percentage of at-risk employees is low, certain communities, such as Belvedere, Alameda, and Crescent City, have high percentages of their local workforce in the tsunami-inundation zone. Employees in the tsunami-inundation zone are primarily in businesses associated with tourism (for example, accommodations, food services, and retail trade) and shipping (for example, transportation and warehousing, manufacturing, and wholesale trade), although the dominance of these sectors varies substantially among the 94 cities. Although the number of occupants is not known for each site, the tsunami-inundation zone contains numerous dependent-population facilities, such as schools and child daycare centers, which may have individuals with limited mobility. The tsunami-inundation zone includes a substantial number of facilities that provide community services, such as banks, religious organizations, and grocery stores, where local residents may be unaware of evacuation procedures if previous awareness efforts focused on home preparedness. There are also numerous recreational areas in the tsunami-inundation zone, such as amusement parks, marinas, city and county beaches, and State and national parks, which attract visitors who may not be aware of tsunami hazards or evacuation procedures. During peak summer months, estimated daily attendance at city and county beaches can be approximately six times larger than the total number of residents in the tsunami-inundation zone. Community exposure to tsunamis in California varies considerably—some communities may experience great losses that reflect only a small part of their community and others may experience relatively small losses that devastate them. Among 94 incorporated communities and the remaining unincorporated areas of the 20 coastal counties, the communities of Alameda, Oakland, Long Beach, Los Angeles, Huntington Beach, and San Diego have the highest number of people and businesses in the tsunami-inundation zone. The communities of Belvedere, Alameda, Crescent City, Emeryville, Seal Beach, and Sausalito have the highest percentages of people and businesses in this zone. On the basis of a composite index, the cities of Alameda, Belvedere, Crescent City, Emeryville, Oakland, and Long Beach have the highest combinations of the number and percentage of people and businesses in tsunami-prone areas.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125222","collaboration":"Prepared in cooperation with the California Emergency Management Agency and the California Geological Survey","usgsCitation":"Wood, N.J., Ratliff, J., and Peters, J., 2013, Community exposure to tsunami hazards in California: U.S. Geological Survey Scientific Investigations Report 2012-5222, iv, 49 p., https://doi.org/10.3133/sir20125222.","productDescription":"iv, 49 p.","startPage":"i","endPage":"49","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":267900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5222.gif"},{"id":267898,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5222/"},{"id":267899,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5222/sir2012-5222.pdf"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.0 ], [ -114.13,42.0 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512741fde4b07fa41a6044ce","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":474345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ratliff, Jamie","contributorId":102915,"corporation":false,"usgs":true,"family":"Ratliff","given":"Jamie","email":"","affiliations":[],"preferred":false,"id":474347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":474346,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043710,"text":"70043710 - 2013 - Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection","interactions":[],"lastModifiedDate":"2018-09-13T10:20:27","indexId":"70043710","displayToPublicDate":"2013-02-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Predictive models for <i>Escherichia coli</i> concentrations at inland lake beaches and relationship of model variables to pathogen detection","title":"Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection","docAbstract":"Predictive models, based on environmental and water quality variables, have been used to improve the timeliness and accuracy of recreational water quality assessments, but their effectiveness has not been studied in inland waters. Sampling at eight inland recreational lakes in Ohio was done in order to investigate using predictive models for <i>Escherichia coli</i> and to understand the links between <i>E. coli</i> concentrations, predictive variables, and pathogens. Based upon results from 21 beach sites, models were developed for 13 sites, and the most predictive variables were rainfall, wind direction and speed, turbidity, and water temperature. Models were not developed at sites where the <i>E. coli</i> standard was seldom exceeded. Models were validated at nine sites during an independent year. At three sites, the model resulted in increased correct responses, sensitivities, and specificities compared to use of the previous day's <i>E. coli</i> concentration (the current method). Drought conditions during the validation year precluded being able to adequately assess model performance at most of the other sites. <i>Cryptosporidium</i>, adenovirus, <i>eaeA</i> (<i>E. coli</i>), <i>ipaH</i> (<i>Shigella</i>), and <i>spvC</i> (<i>Salmonella</i>) were found in at least 20% of samples collected for pathogens at five sites. The presence or absence of the three bacterial genes was related to some of the model variables but was not consistently related to <i>E. coli</i> concentrations. Predictive models were not effective at all inland lake sites; however, their use at two lakes with high swimmer densities will provide better estimates of public health risk than current methods and will be a valuable resource for beach managers and the public.","language":"English","publisher":"American Society for Microbiology","publisherLocation":"Washington, D.C.","doi":"10.1128/AEM.02995-12","usgsCitation":"Francy, D.S., Stelzer, E.A., Duris, J.W., Brady, A., Harrison, J.H., Johnson, H., and Ware, M.W., 2013, Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection: Applied and Environmental Microbiology, v. 79, no. 5, p. 1676-1688, https://doi.org/10.1128/AEM.02995-12.","productDescription":"13 p.","startPage":"1676","endPage":"1688","ipdsId":"IP-032379","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":473950,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1128/aem.02995-12","text":"External Repository"},{"id":267893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267892,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1128/AEM.02995-12"}],"country":"United States","state":"Ohio","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.8203,38.4034 ], [ -84.8203,41.9773 ], [ -80.5182,41.9773 ], [ -80.5182,38.4034 ], [ -84.8203,38.4034 ] ] ] } } ] }","volume":"79","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51274202e4b07fa41a6044de","contributors":{"authors":[{"text":"Francy, Donna S. 0000-0001-9229-3557 dsfrancy@usgs.gov","orcid":"https://orcid.org/0000-0001-9229-3557","contributorId":1853,"corporation":false,"usgs":true,"family":"Francy","given":"Donna","email":"dsfrancy@usgs.gov","middleInitial":"S.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stelzer, Erin A. 0000-0001-7645-7603 eastelzer@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":1933,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin","email":"eastelzer@usgs.gov","middleInitial":"A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duris, Joseph W. 0000-0002-8669-8109 jwduris@usgs.gov","orcid":"https://orcid.org/0000-0002-8669-8109","contributorId":1981,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph","email":"jwduris@usgs.gov","middleInitial":"W.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":474136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brady, Amie M. G.","contributorId":29774,"corporation":false,"usgs":true,"family":"Brady","given":"Amie M. G.","affiliations":[],"preferred":false,"id":474138,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrison, John H.","contributorId":34011,"corporation":false,"usgs":true,"family":"Harrison","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":474139,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Heather E.","contributorId":207837,"corporation":false,"usgs":false,"family":"Johnson","given":"Heather E.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":12456,"text":"former USGS scientist","active":true,"usgs":false}],"preferred":false,"id":744844,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ware, Michael W.","contributorId":65357,"corporation":false,"usgs":true,"family":"Ware","given":"Michael","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":474140,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70043751,"text":"70043751 - 2013 - Disease in a dynamic landscape: host behavior and wildfire reduce amphibian chytrid infection","interactions":[],"lastModifiedDate":"2013-02-21T13:40:17","indexId":"70043751","displayToPublicDate":"2013-02-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Disease in a dynamic landscape: host behavior and wildfire reduce amphibian chytrid infection","docAbstract":"Disturbances are often expected to magnify effects of disease, but these effects may depend on the ecology, behavior, and life history of both hosts and pathogens. In many ecosystems, wildfire is the dominant natural disturbance and thus could directly or indirectly affect dynamics of many diseases. To determine how probability of infection by the aquatic fungus <i>Batrachochytrium dendrobatidis</i> (Bd) varies relative to habitat use by individuals, wildfire, and host characteristics, we sampled 404 boreal toads (<i>Anaxyrus boreas boreas</i>) across Glacier National Park, Montana (USA). Bd causes chytridiomycosis, an emerging infectious disease linked with widespread amphibian declines, including the boreal toad. Probability of infection was similar for females and the combined group of males and juveniles. However, only 9% of terrestrial toads were infected compared to >30% of aquatic toads, and toads captured in recently burned areas were half as likely to be infected as toads in unburned areas. We suspect these large differences in infection reflect habitat choices by individuals that affect pathogen exposure and persistence, especially in burned forests where warm, arid conditions could limit Bd growth. Our results show that natural disturbances such as wildfire and the resulting diverse habitats can influence infection across large landscapes, potentially maintaining local refuges and host behaviors that facilitate evolution of disease resistance.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Conservation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.biocon.2012.09.013","usgsCitation":"Hossack, B.R., Lowe, W., Ware, J.L., and Corn, P., 2013, Disease in a dynamic landscape: host behavior and wildfire reduce amphibian chytrid infection: Biological Conservation, v. 157, p. 293-299, https://doi.org/10.1016/j.biocon.2012.09.013.","productDescription":"7 p.","startPage":"293","endPage":"299","ipdsId":"IP-036149","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":267891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267890,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.biocon.2012.09.013"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.48,48.23 ], [ -114.48,49.0 ], [ -113.24,49.0 ], [ -113.24,48.23 ], [ -114.48,48.23 ] ] ] } } ] }","volume":"157","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51274200e4b07fa41a6044d6","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":474208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Winsor H.","contributorId":64532,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor H.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":474210,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ware, Joy L.","contributorId":28142,"corporation":false,"usgs":true,"family":"Ware","given":"Joy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":474209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Corn, Paul Stephen 0000-0002-4106-6335","orcid":"https://orcid.org/0000-0002-4106-6335","contributorId":107379,"corporation":false,"usgs":true,"family":"Corn","given":"Paul Stephen","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":474211,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043862,"text":"fs20123147 - 2013 - Assessment of undiscovered conventional oil and gas resources of North Africa, 2012","interactions":[],"lastModifiedDate":"2013-02-21T13:25:34","indexId":"fs20123147","displayToPublicDate":"2013-02-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-3147","title":"Assessment of undiscovered conventional oil and gas resources of North Africa, 2012","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated means of 19 billion barrels of technically recoverable undiscovered conventional oil and 370 trillion cubic feet of undiscovered conventional natural gas resources in 8 geologic provinces of North Africa.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123147","collaboration":"World Petroleum Resources Project","usgsCitation":"Schenk, C.J., Klett, T., Whidden, K.J., Kirschbaum, M.A., Charpentier, R., Cook, T.A., Brownfield, M.E., and Pitman, J.K., 2013, Assessment of undiscovered conventional oil and gas resources of North Africa, 2012: U.S. Geological Survey Fact Sheet 2012-3147, 4 p., https://doi.org/10.3133/fs20123147.","productDescription":"4 p.","startPage":"1","endPage":"4","numberOfPages":"4","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":267887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3147.gif"},{"id":267885,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3147/"},{"id":267886,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3147/FS12-3147.pdf"}],"otherGeospatial":"North Africa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -15.0,45.0 ], [ -15.0,15.0 ], [ 40.0,15.0 ], [ 40.0,45.0 ], [ -15.0,45.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512741e3e4b07fa41a6044ca","contributors":{"authors":[{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":474322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klett, Timothy R. 0000-0001-9779-1168 tklett@usgs.gov","orcid":"https://orcid.org/0000-0001-9779-1168","contributorId":709,"corporation":false,"usgs":true,"family":"Klett","given":"Timothy R.","email":"tklett@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":474320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":474325,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirschbaum, Mark A.","contributorId":25112,"corporation":false,"usgs":true,"family":"Kirschbaum","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474326,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Charpentier, Ronald R. charpentier@usgs.gov","contributorId":934,"corporation":false,"usgs":true,"family":"Charpentier","given":"Ronald R.","email":"charpentier@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":474323,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cook, Troy A.","contributorId":52519,"corporation":false,"usgs":true,"family":"Cook","given":"Troy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474327,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":474324,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":474321,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70043802,"text":"70043802 - 2013 - Using hand proportions to test taxonomic boundaries within the <i>Tupaia glis</i> species complex (Scandentia, Tupaiidae)","interactions":[],"lastModifiedDate":"2013-02-21T14:06:21","indexId":"70043802","displayToPublicDate":"2013-02-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Using hand proportions to test taxonomic boundaries within the <i>Tupaia glis</i> species complex (Scandentia, Tupaiidae)","docAbstract":"Treeshrews (order Scandentia) comprise 2 families of squirrel-sized terrestrial, arboreal, and scansorial mammals distributed throughout much of tropical South and Southeast Asia. The last comprehensive taxonomic revision of treeshrews was published in 1913, and a well-supported phylogeny clarifying relationships among all currently recognized extant species within the order has only recently been published. Within the family Tupaiidae, 2 widely distributed species, the northern treeshrew, <i>Tupaia belangeri</i> (Wagner, 1841), and the common treeshrew, <i>T. glis</i> (Diard, 1820), represent a particularly vexing taxonomic complex. These 2 species are currently distinguished primarily based on their respective distributions north and south of the Isthmus of Kra on the Malay Peninsula and on their different mammae counts. This problematic species complex includes 54 published synonyms, many of which represent putative island endemics. The widespread <i>T. glis</i> and <i>T. belangeri</i> collectively comprise a monophyletic assemblage representing the sister lineage to a clade composed of the golden-bellied treeshrew, <i>T. chrysogaster</i> Miller, 1903 (Mentawai Islands), and the long-footed treeshrew, <i>T. longipes</i> (Thomas, 1893) (Borneo). As part of a morphological investigation of the <i>T. glis</i>–<i>T. belangeri</i> complex, we studied the proportions of hand bones, which have previously been shown to be useful in discriminating species of soricids (true shrews). We measured 38 variables from digital X-ray images of 148 museum study skins representing several subspecies of <i>T. glis</i>, <i>T. belangeri</i>, <i>T. chrysogaster</i>, and <i>T. longipes</i> and analyzed these data using principal components and cluster analyses. Manus proportions among these 4 species readily distinguish them, particularly in the cases of <i>T. chrysogaster</i> and <i>T. longipes</i>. We then tested the distinctiveness of several of the populations comprising <i>T. glis</i> and <i>T. longipes</i>. <i>T. longipes longipes</i> and <i>T. l. salatana</i> Lyon, 1913, are distinguishable from each other, and populations of <i>T. \"glis\"</i> from Bangka Island and Sumatra are distinct from those on the Malay Peninsula, supporting the recognition of <i>T. salatana</i>, <i>T. discolor</i> Lyon, 1906, and <i>T. ferruginea</i> Raffles, 1821 as distinct species in Indonesia. These relatively small, potentially vulnerable treeshrew populations occur in the Sundaland biodiversity hotspot and will require additional study to determine their appropriate conservation status.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Mammalogy","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Mammalogists","publisherLocation":"Lawrence, KS","doi":"10.1644/11-MAMM-A-343.1","usgsCitation":"Sargos, E.J., Woodman, N., Reese, A.T., and Olson, L., 2013, Using hand proportions to test taxonomic boundaries within the <i>Tupaia glis</i> species complex (Scandentia, Tupaiidae): Journal of Mammalogy, v. 94, no. 1, p. 183-201, https://doi.org/10.1644/11-MAMM-A-343.1.","productDescription":"19 p.","startPage":"183","endPage":"201","ipdsId":"IP-041158","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473948,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1644/11-mamm-a-343.1","text":"Publisher Index Page"},{"id":267895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267894,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1644/11-MAMM-A-343.1"}],"country":"United States","volume":"94","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51274203e4b07fa41a6044e2","contributors":{"authors":[{"text":"Sargos, Eric J.","contributorId":11091,"corporation":false,"usgs":true,"family":"Sargos","given":"Eric","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":474246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":474245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reese, Aspen T.","contributorId":23826,"corporation":false,"usgs":true,"family":"Reese","given":"Aspen","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":474247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olson, Link E.","contributorId":60927,"corporation":false,"usgs":true,"family":"Olson","given":"Link E.","affiliations":[],"preferred":false,"id":474248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043711,"text":"70043711 - 2013 - Comparison of filters for concentrating microbial indicators and pathogens in lake-water samples","interactions":[],"lastModifiedDate":"2017-02-17T15:10:19","indexId":"70043711","displayToPublicDate":"2013-02-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of filters for concentrating microbial indicators and pathogens in lake-water samples","docAbstract":"<p>Bacterial indicators are used to indicate increased health risk from pathogens and to make beach closure and advisory decisions; however, beaches are seldom monitored for the pathogens themselves. Studies of sources and types of pathogens at beaches are needed to improve estimates of swimming-associated health risks. It would be advantageous and cost-effective, especially for studies conducted on a regional scale, to use a method that can simultaneously filter and concentrate all classes of pathogens from the large volumes of water needed to detect pathogens. In seven recovery experiments, stock cultures of viruses and protozoa were seeded into 10-liter lake water samples, and concentrations of naturally occurring bacterial indicators were used to determine recoveries. For the five filtration methods tested, the highest median recoveries were as follows: glass wool for adenovirus (4.7%); NanoCeram for enterovirus (14.5%) and MS2 coliphage (84%); continuous-flow centrifugation (CFC) plus Virocap (CFC+ViroCap) for <i>Escherichia coli</i> (68.3%) and <i>Cryptosporidium</i> (54%); automatic ultrafiltration (UF) for norovirus GII (2.4%); and dead-end UF for <i>Enterococcus faecalis</i> (80.5%), avian influenza virus (0.02%), and <i>Giardia</i> (57%). In evaluating filter performance in terms of both recovery and variability, the automatic UF resulted in the highest recovery while maintaining low variability for all nine microorganisms. The automatic UF was used to demonstrate that filtration can be scaled up to field deployment and the collection of 200-liter lake water samples.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied and Environmental Microbiology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society for Microbiology","publisherLocation":"Washington, D.C.","doi":"10.1128/AEM.03117-12","usgsCitation":"Francy, D.S., Stelzer, E.A., Brady, A., Huitger, C., Bushon, R.N., Ip, S., Ware, M.W., Villegas, E.N., Gallardo, V., and Lindquist, H.A., 2013, Comparison of filters for concentrating microbial indicators and pathogens in lake-water samples: Applied and Environmental Microbiology, v. 79, no. 4, p. 1342-1352, https://doi.org/10.1128/AEM.03117-12.","productDescription":"11 p.","startPage":"1342","endPage":"1352","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-036134","costCenters":[{"id":456,"text":"National Wildlife Health 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G.","contributorId":29774,"corporation":false,"usgs":true,"family":"Brady","given":"Amie M. G.","affiliations":[],"preferred":false,"id":474146,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huitger, Carrie","contributorId":86242,"corporation":false,"usgs":true,"family":"Huitger","given":"Carrie","affiliations":[],"preferred":false,"id":474150,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bushon, Rebecca N. rnbushon@usgs.gov","contributorId":2304,"corporation":false,"usgs":true,"family":"Bushon","given":"Rebecca","email":"rnbushon@usgs.gov","middleInitial":"N.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474144,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ip, S. 0000-0003-4844-7533 hip@usgs.gov","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":727,"corporation":false,"usgs":true,"family":"Ip","given":"S.","email":"hip@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":474141,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ware, Michael W.","contributorId":65357,"corporation":false,"usgs":true,"family":"Ware","given":"Michael","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":474149,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Villegas, Eric N.","contributorId":56947,"corporation":false,"usgs":true,"family":"Villegas","given":"Eric","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":474148,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gallardo, Vincent","contributorId":7585,"corporation":false,"usgs":true,"family":"Gallardo","given":"Vincent","email":"","affiliations":[],"preferred":false,"id":474145,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lindquist, H.D. Alan","contributorId":48666,"corporation":false,"usgs":true,"family":"Lindquist","given":"H.D.","email":"","middleInitial":"Alan","affiliations":[],"preferred":false,"id":474147,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70044218,"text":"70044218 - 2013 - Distribution of invasive ants and methods for their control in Hawai'i Volcanoes National Park","interactions":[],"lastModifiedDate":"2018-01-05T12:37:34","indexId":"70044218","displayToPublicDate":"2013-02-20T14:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-040","title":"Distribution of invasive ants and methods for their control in Hawai'i Volcanoes National Park","docAbstract":"<div class=\"page\" title=\"Page 8\">\n<div class=\"layoutArea\">\n<div class=\"column\">\n<p><span>The first invasive ants were detected in Hawai`i Volcanoes National Park (HAVO) more than 80 years ago. Ecological impacts of these ants are largely unknown, but studies in Hawai`i and elsewhere increasingly show that invasive ants can reduce abundance and diversity of native arthropod communities as well as disrupt pollination and food webs. Prior to the present study, knowledge of ant distributions in HAVO has primarily been restricted to road- and trail-side </span><span>surveys of the Kīlauea and Mauna Loa Strip sections of the park. </span><span>Due to the risks that ants pose to HAVO resources, understanding their distributions and identifying tools to eradicate or control populations of the most aggressive species is an important objective of park managers. We mapped ant distributions in two of the most intensively managed sections of the park, Mauna Loa Strip and Kahuku. We also tested the efficacy of baits to control the Argentine ant (<i>Linepithema humile</i>) and the big-headed ant (<i>Pheidole megacephala</i>), two of the most aggressive and ecologically destructive species in Hawai`i. Efficacy testing of formicidal bait was designed to provide park managers with options for eradicating small populations or controlling populations that occur at levels beyond which they can be eradicated. </span></p>\n<p><span>Within the Mauna Loa Strip and Kahuku sections of HAVO we conducted systematic surveys of ant distributions at 1625 stations covering nearly 200 km of roads, fences, and transects between August 2008 and April 2010. Overall, 15 ant species were collected in the two areas, with 12 being found on Mauna Loa Strip and 11 at Kahuku. <i>Cardiocondyla kagutsuchi</i> was most widespread at both sites, ranging in elevation from 920 to 2014 m, and was the only species found above 1530 m. Argentine ants and big-headed ants were also found in both areas, but their distributions did not overlap. Surveys of Argentine ants identified areas of infestation covering 560 ha at Mauna Loa Strip and 585 ha at Kahuku. At both sites, upper boundaries of big-headed ants coincided with lower boundaries of Argentine ants. Significantly, <i>Wasmannia auropunctata</i> (little fire ant) was not detected during our surveys. </span></p>\n<p><span>Formicidal baits tested for controlling Argentine ants included Xstinguish<sup>TM</sup> (containing fipronil at 0.01%), Maxforce</span><sup><span>&reg; </span></sup><span>(hydramethylnon 1.0%), and Australian Distance</span><sup><span>&reg; </span></sup><span>(pyriproxyfen 0.5%). Each bait was distributed evenly over four 2500 m</span><sup><span>2 </span></sup><span>replicate plots. Applications were repeated approximately four weeks after the initial treatment. Plots were subdivided into 25 subplots and ants monitored within each subplot using paper cards containing tuna bait at approximately one week intervals for about 14 weeks. All treatments reduced ant numbers, but none eradicated ants on any of the plots. Xstinguish<sup>TM</sup> produced a strong and lasting effect, depressing ant abundance below 1% of control plot levels within the first week and for about eight weeks afterward. Maxforce</span><sup><span>&reg; </span></sup><span>was slower to attain maximum effectiveness, reducing ants to 8% of control levels after one week and 3% after six weeks. Australian Distance</span><sup><span>&reg; </span></sup><span>was least effective, decreasing ant abundance to 19% of control levels after one week with numbers subsequently rebounding to 40% of controls at four weeks and 72% at 10 weeks. In measurements of the proportion of bait cards at which ants were detected, Xstinguish<sup>TM</sup> clearly out-performed Maxforce</span><sup><span>&reg;</span></sup><span>, reaching a minimum detection rate of 3% of bait cards at one week compared to a low of 19% for Maxforce</span><sup><span>&reg; </span></sup><span>two weeks following the second treatment. Although ant abundances were dramatically reduced on Xstinguish<sup>TM</sup> plots, it is not currently registered for use in the USA. Our results suggest that ant abundance can be greatly reduced using registered baits, but further research is needed before even small-scale eradication of Argentine ants can be achieved.&nbsp;</span></p>\n<div class=\"page\" title=\"Page 9\">\n<div class=\"layoutArea\">\n<div class=\"column\">\n<p><span>Formicidal baits tested to control big-headed ants included Amdro</span><sup><span>&reg; </span></sup><span>(hydramethylnon 0.75%), Xstinguish<sup>TM</sup> (fipronil 0.01%), Extinguish</span><sup><span>&reg; </span></sup><span>Plus (a blend of hydramethylnon 0.365% and S- methoprene 0.25%), and Australian Distance</span><sup><span>&reg; </span></sup><span>Plus (hydramethylnon 0.365% and pyriproxyfen 0.25%). Application methods were the same as used for Argentine ants, with baits being applied on two occasions (approximately four weeks apart) on four 2500 m</span><sup><span>2 </span></sup><span>replicate plots. All four baits reduced populations to below 2% of control plot levels within one week of treatment. Amdro</span><sup><span>&reg; </span></sup><span>was particularly effective as no ants were detected on two of the four Amdro</span><sup><span>&reg; </span></sup><span>plots immediately following treatment. Suppression was long-lived in three of the treatments; Amdro</span><sup><span>&reg;</span></sup><span>, Australian Distance</span><sup><span>&reg; </span></sup><span>Plus, and Extinguish</span><sup><span>&reg; </span></sup><span>Plus all maintained ant abundances at levels less than 1% of control plots over 12 weeks of study. In contrast, ant abundances in Xstinguish<sup>TM</sup> plots rose to 7% of control plots after four weeks and 20% after 10 weeks. Our results corroborate other recent studies indicating that small populations of big-headed ants can be controlled in natural areas using products registered in the USA.&nbsp;</span></p>\n</div>\n</div>\n</div>\n</div>\n</div>\n</div>","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Peck, R.W., Banko, P.C., Snook, K., and Euaparadorn, M., 2013, Distribution of invasive ants and methods for their control in Hawai'i Volcanoes National Park: Technical Report HCSU-040, v, 48 p.","productDescription":"v, 48 p.","numberOfPages":"55","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042832","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328013,"type":{"id":15,"text":"Index Page"},"url":"https://dspace.lib.hawaii.edu/handle/10790/2626"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.8026123046875,\n              19.066011797810056\n            ],\n            [\n              -155.8026123046875,\n              19.303367019780328\n            ],\n            [\n              -155.46890258789062,\n              19.303367019780328\n            ],\n            [\n              -155.46890258789062,\n              19.066011797810056\n            ],\n            [\n              -155.8026123046875,\n              19.066011797810056\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.42221069335938,\n              19.399249278602312\n            ],\n            [\n              -155.42221069335938,\n              19.651640912520307\n            ],\n            [\n              -155.09674072265625,\n              19.651640912520307\n            ],\n            [\n              -155.09674072265625,\n              19.399249278602312\n            ],\n            [\n              -155.42221069335938,\n              19.399249278602312\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad45e4b05e859bdfb8cf","contributors":{"authors":[{"text":"Peck, Robert W.","contributorId":45629,"corporation":false,"usgs":true,"family":"Peck","given":"Robert","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":644978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":644979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Snook, Kirsten","contributorId":173527,"corporation":false,"usgs":false,"family":"Snook","given":"Kirsten","email":"","affiliations":[],"preferred":false,"id":644980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Euaparadorn, Melody","contributorId":119927,"corporation":false,"usgs":true,"family":"Euaparadorn","given":"Melody","email":"","affiliations":[],"preferred":false,"id":644981,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70188512,"text":"70188512 - 2013 - Where fast weathering creates thin regolith and slow weathering creates thick regolith","interactions":[],"lastModifiedDate":"2017-06-14T13:47:53","indexId":"70188512","displayToPublicDate":"2013-02-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Where fast weathering creates thin regolith and slow weathering creates thick regolith","docAbstract":"<p>Weathering disaggregates rock into regolith – the fractured or granular earth material that sustains life on the continental land surface. Here, we investigate what controls the depth of regolith formed on ridges of two rock compositions with similar initial porosities in Virginia (USA). A priori, we predicted that the regolith on diabase would be thicker than on granite because the dominant mineral (feldspar) in the diabase weathers faster than its granitic counterpart. However, weathering advanced 20\u0001 deeper into the granite than the diabase. The 20 \u0001 -thicker regolith is attributed mainly to connected micron-sized pores, microfractures formed around oxidizing biotite at 20 m depth, and the lower iron (Fe) content in the felsic rock. Such porosity allows pervasive advection and deep oxidation in the granite. These observations may explain why regolith worldwide is thicker on felsic compared to mafic rock under similar conditions. To understand regolith formation will require better understanding of such deep oxidation reactions and how they impact fluid flow during weathering.</p>","language":"English","publisher":"Wiley Online ","doi":"10.1002/esp.3369","usgsCitation":"Bazilevskaya, E., Lebedeva, M., Pavich, M.J., Brantley, S.L., Rother, G., Parkinson, D.Y., and Cole, D., 2013, Where fast weathering creates thin regolith and slow weathering creates thick regolith: Earth Surface Processes and Landforms, p. 847-858, https://doi.org/10.1002/esp.3369.","productDescription":"12 p. ","startPage":"847","endPage":"858","ipdsId":"IP-042800","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States ","state":"Virginia 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,{"id":70043831,"text":"sir20125275 - 2013 - Hydrogeologic framework and estimates of groundwater storage for the Hualapai Valley, Detrital Valley, and Sacramento Valley basins, Mohave County, Arizona","interactions":[],"lastModifiedDate":"2013-02-20T16:12:11","indexId":"sir20125275","displayToPublicDate":"2013-02-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5275","title":"Hydrogeologic framework and estimates of groundwater storage for the Hualapai Valley, Detrital Valley, and Sacramento Valley basins, Mohave County, Arizona","docAbstract":"We have investigated the hydrogeology of the Hualapai Valley, Detrital Valley, and Sacramento Valley basins of Mohave County in northwestern Arizona to develop a better understanding of groundwater storage within the basin fill aquifers. In our investigation we used geologic maps, well-log data, and geophysical surveys to delineate the sedimentary textures and lithology of the basin fill. We used gravity data to construct a basin geometry model that defines smaller subbasins within the larger basins, and airborne transient-electromagnetic modeled results along with well-log lithology data to infer the subsurface distribution of basin fill within the subbasins. Hydrogeologic units (HGUs) are delineated within the subbasins on the basis of the inferred lithology of saturated basin fill. We used the extent and size of HGUs to estimate groundwater storage to depths of 400 meters (m) below land surface (bls). The basin geometry model for the Hualapai Valley basin consists of three subbasins: the Kingman, Hualapai, and southern Gregg subbasins. In the Kingman subbasin, which is estimated to be 1,200 m deep, saturated basin fill consists of a mixture of fine- to coarse-grained sedimentary deposits. The Hualapai subbasin, which is the largest of the subbasins, contains a thick halite body from about 400 m to about 4,300 m bls. Saturated basin fill overlying the salt body consists predominately of fine-grained older playa deposits. In the southern Gregg subbasin, which is estimated to be 1,400 m deep, saturated basin fill is interpreted to consist primarily of fine- to coarse-grained sedimentary deposits. Groundwater storage to 400 m bls in the Hualapai Valley basin is estimated to be 14.1 cubic kilometers (km<sup>3</sup>). The basin geometry model for the Detrital Valley basin consists of three subbasins: northern Detrital, central Detrital, and southern Detrital subbasins. The northern and central Detrital subbasins are characterized by a predominance of playa evaporite and fine-grained clastic deposits; evaporite deposits in the northern Detrital subbasin include halite. The northern Detrital subbasin is estimated to be 600 m deep and the middle Detrital subbasin is estimated to be 700 m deep. The southern Detrital subbasin, which is estimated to be 1,500 m deep, is characterized by a mixture of fine- to coarse-grained basin fill deposits. Groundwater storage to 400 m bls in the Detrital Valley basin is estimated to be 9.8 km<sup>3</sup>. The basin geometry model for the Sacramento Valley basin consists of three subbasins: the Chloride, Golden Valley, and Dutch Flat subbasins. The Chloride subbasin, which is estimated to be 900 m deep, is characterized by fine- to coarse-grained basin fill deposits. In the Golden Valley subbasin, which is elongated north-south, and is estimated to be 1,300 m deep, basin fill includes fine-grained sedimentary deposits overlain by coarse-grained sedimentary deposits in much of the subbasin. The Dutch Flat subbasin is estimated to be 2,600 m deep, and well-log lithologic data suggest that the basin fill consists of interlayers of gravel, sand, and clay. Groundwater storage to 400 m bls in the Sacramento Valley basin is estimated to be 35.1 km<sup>3</sup>.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125275","collaboration":"Prepared in cooperation with the Arizona Department of Water Resources and Mohave County, Arizona","usgsCitation":"Truini, M., Beard, L.S., Kennedy, J., and Anning, D., 2013, Hydrogeologic framework and estimates of groundwater storage for the Hualapai Valley, Detrital Valley, and Sacramento Valley basins, Mohave County, Arizona: U.S. Geological Survey Scientific Investigations Report 2012-5275, vi, 47 p., https://doi.org/10.3133/sir20125275.","productDescription":"vi, 47 p.","startPage":"i","endPage":"47","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":267851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5275.gif"},{"id":267850,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5275/"},{"id":267849,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5275/sir2012-5275.pdf"}],"country":"United States","state":"Arizona","county":"Mohave County","otherGeospatial":"Hualapai Valley;Detrital Valley;Sacramento Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.82,31.33 ], [ -114.82,37.0 ], [ -109.0,37.0 ], [ -109.0,31.33 ], [ -114.82,31.33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5125f086e4b09d00759cd054","contributors":{"authors":[{"text":"Truini, Margot mtruini@usgs.gov","contributorId":599,"corporation":false,"usgs":true,"family":"Truini","given":"Margot","email":"mtruini@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beard, L. Sue","contributorId":87607,"corporation":false,"usgs":true,"family":"Beard","given":"L.","email":"","middleInitial":"Sue","affiliations":[],"preferred":false,"id":474284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Jeffrey 0000-0002-3365-6589","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":101124,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","affiliations":[],"preferred":false,"id":474285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anning, Dave W.","contributorId":36025,"corporation":false,"usgs":true,"family":"Anning","given":"Dave W.","affiliations":[],"preferred":false,"id":474283,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043829,"text":"ofr20131037 - 2013 - Potential for recovery of cerium contained in automotive catalytic converters","interactions":[],"lastModifiedDate":"2013-02-20T15:44:41","indexId":"ofr20131037","displayToPublicDate":"2013-02-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1037","title":"Potential for recovery of cerium contained in automotive catalytic converters","docAbstract":"Catalytic converters (CATCONs) are required by Federal law to be installed in nearly all gasoline- and diesel-fueled onroad vehicles used in the United States. About 85 percent of the light-duty vehicles and trucks manufactured worldwide are equipped with CATCONs. Portions of the CATCONs (called monoliths) are recycled for their platinum-group metal (PGM) content and for the value of the stainless steel they contain. The cerium contained in the monoliths, however, is disposed of along with the slag produced from the recycling process. Although there is some smelter capacity in the United States to treat the monoliths in order to recover the PGMs, a great percentage of monoliths is exported to Europe and South Africa for recycling, and a lesser amount is exported to Japan. There is presently no commercial-scale capacity in place domestically to recover cerium from the monoliths. Recycling of cerium or cerium compounds from the monoliths could help ensure against possible global supply shortages by increasing the amount that is available in the supply chain as well as the number and geographic distribution of the suppliers. It could also reduce the amount of material that goes into landfills. Also, the additional supply could lower the price of the commodity. This report analyzes how much cerium oxide is contained in CATCONs and how much could be recovered from used CATCONs.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131037","usgsCitation":"Bleiwas, D.I., 2013, Potential for recovery of cerium contained in automotive catalytic converters: U.S. Geological Survey Open-File Report 2013-1037, iv, 10 p., https://doi.org/10.3133/ofr20131037.","productDescription":"iv, 10 p.","startPage":"i","endPage":"10","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":267845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1037.jpg"},{"id":267843,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1037/"},{"id":267844,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1037/OFR2013-1037.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5125f088e4b09d00759cd05c","contributors":{"authors":[{"text":"Bleiwas, Donald I. bleiwas@usgs.gov","contributorId":1434,"corporation":false,"usgs":true,"family":"Bleiwas","given":"Donald","email":"bleiwas@usgs.gov","middleInitial":"I.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":474277,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70043830,"text":"ofr20131035 - 2013 - Conservation and Ecology of Marine Forage Fishes--Proceedings of a Research Symposium, September 2012","interactions":[],"lastModifiedDate":"2013-02-20T15:55:49","indexId":"ofr20131035","displayToPublicDate":"2013-02-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1035","title":"Conservation and Ecology of Marine Forage Fishes--Proceedings of a Research Symposium, September 2012","docAbstract":"Locally and globally, there is growing recognition of the critical roles that herring, smelt, sand lance, eulachon, and other forage fishes play in marine ecosystems. Scientific and resource management entities throughout the Salish Sea, agree that extensive information gaps exist, both in basic biological knowledge and parameters critical to fishery management. Communication and collaboration among researchers also is inadequate. Building on the interest and enthusiasm generated by recent forage fish workshops and symposia around the region, the 2012 <i>Research Symposium on the Conservation and Ecology of Marine Forage Fishes</i> was designed to elucidate practical recommendations for science and policy needs and actions, and spur further collaboration in support for the precautionary management of forage fish. This dynamic and productive event was a joint venture of the Northwest Straits Commission Forage Fish Program, U.S. Geological Survey (USGS), Washington Department of Fish and Wildlife (WDFW), and The Puget Sound Partnership. The symposium was held on September 12–14, 2012, at the University of Washington, Friday Harbor Laboratories campus. Sixty scientists, graduate students, and fisheries policy experts convened; showcasing ongoing research, conservation, and management efforts targeting forage fish from regional and national perspectives. The primary objectives of this event were to: (1) review current research and management related to marine forage fish species; and (2) identify priority science and policy needs and actions for Washington, British Columbia, and the entire West Coast. Given the diversity of knowledge, interests, and disciplines surrounding forage fish on both sides of the international border, the organizing committee made a concerted effort to contact many additional experts who, although unable to attend, provided valuable insights and ideas to the symposium structure and discussions. The value of the symposium format was highlighted in the closing remarks delivered by Joseph Gaydos, SeaDoc Society and Chair of the Puget Sound Science Panel. Dr. Gaydos’ presentation referenced the 2011 paper by Murray Rudd in the journal <i>Conservation Biology</i>, “How research-prioritization exercises affect conservation policy.” The paper points out that policy makers and funding agencies are more likely to gain a full understanding of issues when they are presented with research findings from an aligned research program. That is, compared to unaligned research strategies, where work is not based on identified research priorities.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131035","collaboration":"Prepared in cooperation with the Northwest Straits Commission, the Washington State Department of Fish and Wildlife, and the Puget Sound Partnership","usgsCitation":"Liedtke, T., Gibson, C., Lowry, D., and Fagergren, D., 2013, Conservation and Ecology of Marine Forage Fishes--Proceedings of a Research Symposium, September 2012: U.S. Geological Survey Open-File Report 2013-1035, vi, 24 p., https://doi.org/10.3133/ofr20131035.","productDescription":"vi, 24 p.","startPage":"i","endPage":"24","numberOfPages":"34","additionalOnlineFiles":"N","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":267848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1035.jpg"},{"id":267846,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1035/"},{"id":267847,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1035/pdf/ofr20131035.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5125f05fe4b09d00759cd04c","contributors":{"authors":[{"text":"Liedtke, Theresa","contributorId":91763,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","affiliations":[],"preferred":false,"id":474281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibson, Caroline","contributorId":75401,"corporation":false,"usgs":true,"family":"Gibson","given":"Caroline","email":"","affiliations":[],"preferred":false,"id":474279,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowry, Dayv","contributorId":80563,"corporation":false,"usgs":true,"family":"Lowry","given":"Dayv","email":"","affiliations":[],"preferred":false,"id":474280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fagergren, Duane","contributorId":19445,"corporation":false,"usgs":true,"family":"Fagergren","given":"Duane","email":"","affiliations":[],"preferred":false,"id":474278,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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