Eastern hemlock (Tsuga canadensis [L.]) is the most shade-tolerant and long-lived tree species in eastern North America. The hemlock woolly adelgid (Adelges tsugae) (HWA), is a nonnative invasive insect that feeds on eastern hemlock and Carolina hemlock (Tsuga caroliniana Engelm.). HWA currently is established in 17 eastern states and is causing tree decline and wide-ranging tree mortality. Our data from West Virginia and Pennsylvania suggest that hemlock crown vigor (a ranking of amount of live crown) relates to a predictable pattern of hemlock vulnerability at light and moderate levels of HWA infestation. We found that crown variables, such as live crown ratio and crown density and transparency, are accurate predictors of hemlock decline; more vigorous trees appear to be less vulnerable to HWA. Thus, silvicultural thinning treatments may be a means for reducing stand densities and increasing crown vigor in colder areas where climate may slow HWA spread.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Proceedings from the Conference on the Ecology and Management of High-Elevation Forests in the Central and Southern Appalachian Mountains","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"USDA Forest Service","usgsCitation":"Fajvan, M.A., and Wood, P.B., 2010, Maintenance of Eastern hemlock forests: Factors associated with hemlock vulnerability to hemlock woolly adelgid, in Proceedings from the Conference on the Ecology and Management of High-Elevation Forests in the Central and Southern Appalachian Mountains, p. 31-38.","productDescription":"8 p.","startPage":"31","endPage":"38","ipdsId":"IP-014482","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":348906,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.nrs.fs.fed.us/pubs/gtr/gtr_nrs-p-64.pdf"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a610acee4b06e28e9c256ed","contributors":{"authors":[{"text":"Fajvan, Mary Ann","contributorId":200418,"corporation":false,"usgs":false,"family":"Fajvan","given":"Mary","email":"","middleInitial":"Ann","affiliations":[],"preferred":false,"id":722255,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Petra Bohall pbwood@usgs.gov","contributorId":1791,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"Bohall","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":718524,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70037330,"text":"70037330 - 2010 - Effects of 3D random correlated velocity perturbations on predicted ground motions","interactions":[],"lastModifiedDate":"2016-01-27T15:17:06","indexId":"70037330","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Effects of 3D random correlated velocity perturbations on predicted ground motions","docAbstract":"Three-dimensional, finite-difference simulations of a realistic finite-fault rupture on the southern Hayward fault are used to evaluate the effects of random, correlated velocity perturbations on predicted ground motions. Velocity perturbations are added to a three-dimensional (3D) regional seismic velocity model of the San Francisco Bay Area using a 3D von Karman random medium. Velocity correlation lengths of 5 and 10 km and standard deviations in the velocity of 5% and 10% are considered. The results show that significant deviations in predicted ground velocities are seen in the calculated frequency range (≤1 Hz) for standard deviations in velocity of 5% to 10%. These results have implications for the practical limits on the accuracy of scenario ground-motion calculations and on retrieval of source parameters using higher-frequency, strong-motion data.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford","doi":"10.1785/0120090060","issn":"00371106","usgsCitation":"Hartzell, S., Harmsen, S., and Frankel, A., 2010, Effects of 3D random correlated velocity perturbations on predicted ground motions: Bulletin of the Seismological Society of America, v. 100, no. 4, p. 1415-1426, https://doi.org/10.1785/0120090060.","productDescription":"12 p.","startPage":"1415","endPage":"1426","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":244970,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217058,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120090060"}],"volume":"100","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-07-27","publicationStatus":"PW","scienceBaseUri":"505a0644e4b0c8380cd5119d","contributors":{"authors":[{"text":"Hartzell, S.","contributorId":12603,"corporation":false,"usgs":true,"family":"Hartzell","given":"S.","email":"","affiliations":[],"preferred":false,"id":460503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harmsen, S.","contributorId":79600,"corporation":false,"usgs":true,"family":"Harmsen","given":"S.","affiliations":[],"preferred":false,"id":460505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frankel, A. 0000-0001-9119-6106","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":41593,"corporation":false,"usgs":true,"family":"Frankel","given":"A.","affiliations":[],"preferred":false,"id":460504,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70035302,"text":"70035302 - 2010 - Environmental controls on drainage behavior of an ephemeral stream","interactions":[],"lastModifiedDate":"2018-04-02T15:24:40","indexId":"70035302","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3478,"text":"Stochastic Environmental Research and Risk Assessment","active":true,"publicationSubtype":{"id":10}},"title":"Environmental controls on drainage behavior of an ephemeral stream","docAbstract":"Streambed drainage was measured at the cessation of 26 ephemeral streamflow events in Rillito Creek, Tucson, Arizona from August 2000 to June 2002 using buried time domain reflectometry (TDR) probes. An unusual drainage response was identified, which was characterized by sharp drainage from saturation to near field capacity at each depth with an increased delay between depths. We simulated the drainage response using a variably saturated numerical flow model representing a two-layer system with a high permeability layer overlying a lower permeability layer. Both the observed data and the numerical simulation show a strong correlation between the drainage velocity and the temperature of the stream water. A linear combination of temperature and the no-flow period preceding flow explained about 90% of the measured variations in drainage velocity. Evaluation of this correlative relationship with the one-dimensional numerical flow model showed that the observed temperature fluctuations could not reproduce the magnitude of variation in the observed drainage velocity. Instead, the model results indicated that flow duration exerts the most control on drainage velocity, with the drainage velocity decreasing nonlinearly with increasing flow duration. These findings suggest flow duration is a primary control of water availability for plant uptake in near surface sediments of an ephemeral stream, an important finding for estimating the ecological risk of natural or engineered changes to streamflow patterns. Correlative analyses of soil moisture data, although easy and widely used, can result in erroneous conclusions of hydrologic cause—effect relationships, and demonstrating the need for joint physically-based numerical modeling and data synthesis for hypothesis testing to support quantitative risk analysis.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Stochastic Environmental Research and Risk Assessment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"http://www.springer.com","doi":"10.1007/s00477-010-0398-8","issn":"14363240","usgsCitation":"Blasch, K., Ferre, T., and Vrugt, J., 2010, Environmental controls on drainage behavior of an ephemeral stream: Stochastic Environmental Research and Risk Assessment, v. 24, no. 7, p. 1077-1087, https://doi.org/10.1007/s00477-010-0398-8.","productDescription":"11 p.","startPage":"1077","endPage":"1087","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":243041,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215251,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00477-010-0398-8"}],"country":"United States","state":"Arizona","city":"Tucson","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.0594,31.9917 ], [ -111.0594,32.3202 ], [ -110.7082,32.3202 ], [ -110.7082,31.9917 ], [ -111.0594,31.9917 ] ] ] } } ] }","volume":"24","issue":"7","noUsgsAuthors":false,"publicationDate":"2010-04-27","publicationStatus":"PW","scienceBaseUri":"505a09b5e4b0c8380cd5201f","contributors":{"authors":[{"text":"Blasch, K.W.","contributorId":29877,"corporation":false,"usgs":true,"family":"Blasch","given":"K.W.","affiliations":[],"preferred":false,"id":450088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferre, T.P.A.","contributorId":196167,"corporation":false,"usgs":false,"family":"Ferre","given":"T.P.A.","email":"","affiliations":[],"preferred":false,"id":450089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vrugt, J.A.","contributorId":77378,"corporation":false,"usgs":true,"family":"Vrugt","given":"J.A.","affiliations":[],"preferred":false,"id":450090,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037696,"text":"70037696 - 2010 - Development of a new toxic-unit model for the bioassessment of metals in streams","interactions":[],"lastModifiedDate":"2018-10-10T17:03:54","indexId":"70037696","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Development of a new toxic-unit model for the bioassessment of metals in streams","docAbstract":"Two toxic-unit models that estimate the toxicity of trace-metal mixtures to benthic communities were compared. The chronic criterion accumulation ratio (CCAR), a modification of biotic ligand model (BLM) outputs for use as a toxic-unit model, accounts for the modifying and competitive influences of major cations (Ca2+, Mg2+, Na+, K+, H+), anions (HCO3−, CO32−,SO42−, Cl−, S2−) and dissolved organic carbon (DOC) in determining the free metal ion available for accumulation on the biotic ligand. The cumulative criterion unit (CCU) model, an empirical statistical model of trace-metal toxicity, considers only the ameliorative properties of Ca2+ and Mg2+ (hardness) in determining the toxicity of total dissolved trace metals. Differences in the contribution of a metal (e.g., Cu, Cd, Zn) to toxic units as determined by CCAR or CCU were observed and attributed to how each model incorporates the influences of DOC, pH, and alkalinity. Akaike information criteria demonstrate that CCAR is an improved predictor of benthic macroinvertebrate community metrics as compared with CCU. Piecewise models depict great declines (thresholds) in benthic macroinvertebrate communities at CCAR of 1 or more, while negative changes in benthic communities were detected at a CCAR of less than 1. We observed a 7% reduction in total taxa richness and a 43% decrease in Heptageniid abundance between background (CCAR = 0.1) and the threshold of chronic toxicity on the basis of continuous chronic criteria (CCAR = 1). In this first application of the BLM as a toxic-unit model, we found it superior to CCU.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Toxicology and Chemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/etc.302","issn":"07307268","usgsCitation":"Schmidt, T., Clements, W., Mitchell, K., Church, S.E., Wanty, R.B., Fey, D.L., Verplanck, P.L., and San Juan, C.A., 2010, Development of a new toxic-unit model for the bioassessment of metals in streams: Environmental Toxicology and Chemistry, v. 29, no. 11, p. 2432-2442, https://doi.org/10.1002/etc.302.","productDescription":"11 p.","startPage":"2432","endPage":"2442","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":475786,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.302","text":"Publisher Index Page"},{"id":246004,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218027,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/etc.302"}],"volume":"29","issue":"11","noUsgsAuthors":false,"publicationDate":"2010-07-09","publicationStatus":"PW","scienceBaseUri":"505a003fe4b0c8380cd4f67a","contributors":{"authors":[{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":462345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clements, W.H.","contributorId":78855,"corporation":false,"usgs":true,"family":"Clements","given":"W.H.","email":"","affiliations":[],"preferred":false,"id":462348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, K.A.","contributorId":38825,"corporation":false,"usgs":true,"family":"Mitchell","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":462342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Church, Stanley E. schurch@usgs.gov","contributorId":199165,"corporation":false,"usgs":true,"family":"Church","given":"Stanley","email":"schurch@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":462344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wanty, Richard B. 0000-0002-2063-6423 rwanty@usgs.gov","orcid":"https://orcid.org/0000-0002-2063-6423","contributorId":443,"corporation":false,"usgs":true,"family":"Wanty","given":"Richard","email":"rwanty@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":462346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fey, David L. dfey@usgs.gov","contributorId":713,"corporation":false,"usgs":true,"family":"Fey","given":"David","email":"dfey@usgs.gov","middleInitial":"L.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":462343,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":462349,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"San Juan, Carma A. 0000-0002-9151-1919 csanjuan@usgs.gov","orcid":"https://orcid.org/0000-0002-9151-1919","contributorId":1146,"corporation":false,"usgs":true,"family":"San Juan","given":"Carma","email":"csanjuan@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":462347,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70037617,"text":"70037617 - 2010 - Sedimentary basins reconnaissance using the magnetic Tilt-Depth method","interactions":[],"lastModifiedDate":"2012-03-12T17:22:00","indexId":"70037617","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1612,"text":"Exploration Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Sedimentary basins reconnaissance using the magnetic Tilt-Depth method","docAbstract":"We compute the depth to the top of magnetic basement using the Tilt-Depth method from the best available magnetic anomaly grids covering the continental USA and Australia. For the USA, the Tilt-Depth estimates were compared with sediment thicknesses based on drilling data and show a correlation of 0.86 between the datasets. If random data were used then the correlation value goes to virtually zero. There is little to no lateral offset of the depth of basinal features although there is a tendency for the Tilt-Depth results to be slightly shallower than the drill depths. We also applied the Tilt-Depth method to a local-scale, relatively high-resolution aeromagnetic survey over the Olympic Peninsula of Washington State. The Tilt-Depth method successfully identified a variety of important tectonic elements known from geological mapping. Of particular interest, the Tilt-Depth method illuminated deep (3km) contacts within the non-magnetic sedimentary core of the Olympic Mountains, where magnetic anomalies are subdued and low in amplitude. For Australia, the Tilt-Depth estimates also give a good correlation with known areas of shallow basement and sedimentary basins. Our estimates of basement depth are not restricted to regional analysis but work equally well at the micro scale (basin scale) with depth estimates agreeing well with drill hole and seismic data. We focus on the eastern Officer Basin as an example of basin scale studies and find a good level of agreement between previously-derived basin models. However, our study potentially reveals depocentres not previously mapped due to the sparse distribution of well data. This example thus shows the potential additional advantage of the method in geological interpretation. The success of this study suggests that the Tilt-Depth method is useful in estimating the depth to crystalline basement when appropriate quality aeromagnetic anomaly data are used (i.e. line spacing on the order of or less than the expected depth to basement). The method is especially valuable as a reconnaissance tool in regions where drillhole or seismic information are either scarce, lacking, or ambiguous.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Exploration Geophysics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1071/EG10007","issn":"08123985","usgsCitation":"Salem, A., Williams, S., Samson, E., Fairhead, D., Ravat, D., and Blakely, R., 2010, Sedimentary basins reconnaissance using the magnetic Tilt-Depth method: Exploration Geophysics, v. 41, no. 3, p. 198-209, https://doi.org/10.1071/EG10007.","startPage":"198","endPage":"209","numberOfPages":"12","costCenters":[],"links":[{"id":245881,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217908,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1071/EG10007"}],"volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2018-12-06","publicationStatus":"PW","scienceBaseUri":"505b8a15e4b08c986b317011","contributors":{"authors":[{"text":"Salem, A.","contributorId":47604,"corporation":false,"usgs":true,"family":"Salem","given":"A.","email":"","affiliations":[],"preferred":false,"id":461937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, S.","contributorId":18514,"corporation":false,"usgs":true,"family":"Williams","given":"S.","email":"","affiliations":[],"preferred":false,"id":461936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Samson, E.","contributorId":105569,"corporation":false,"usgs":true,"family":"Samson","given":"E.","email":"","affiliations":[],"preferred":false,"id":461940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fairhead, D.","contributorId":106352,"corporation":false,"usgs":true,"family":"Fairhead","given":"D.","email":"","affiliations":[],"preferred":false,"id":461941,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ravat, D.","contributorId":102971,"corporation":false,"usgs":true,"family":"Ravat","given":"D.","email":"","affiliations":[],"preferred":false,"id":461939,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blakely, R.J. 0000-0003-1701-5236","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":70755,"corporation":false,"usgs":true,"family":"Blakely","given":"R.J.","affiliations":[],"preferred":false,"id":461938,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70046763,"text":"dds49126 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: STATSGO Soil Characteristics","interactions":[],"lastModifiedDate":"2013-11-25T16:06:02","indexId":"dds49126","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"491-26","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: STATSGO Soil Characteristics","docAbstract":"This tabular data set represents estimated soil variables compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The variables included are cation exchange capacity, percent calcium carbonate, slope, water-table depth, soil thickness, hydrologic soil group, soil erodibility (k-factor), permeability, average water capacity, bulk density, percent organic material, percent clay, percent sand, and percent silt. The source data set is the State Soil ( STATSGO ) Geographic Database (Wolock, 1997). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49126","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: STATSGO Soil Characteristics: U.S. Geological Survey Data Series 491-26, Dataset, https://doi.org/10.3133/dds49126.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274427,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_statsgo.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d3f663e4b09630fbdc527d","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480184,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70037669,"text":"70037669 - 2010 - GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa","interactions":[],"lastModifiedDate":"2012-04-30T16:43:33","indexId":"70037669","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa","docAbstract":"Nonpoint source pollution is the leading cause of the U.S.'s water quality problems. One important component of nonpoint source pollution control is an understanding of what and how watershed-scale conditions influence ambient water quality. This paper investigated the use of spatial regression to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration in the Cedar River Watershed, Iowa. An Arc Hydro geodatabase was constructed to organize various datasets on the watershed. Spatial regression models were developed to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration and predict NO3NO2-N concentration at unmonitored locations. Unlike the traditional ordinary least square (OLS) method, the spatial regression method incorporates the potential spatial correlation among the observations in its coefficient estimation. Study results show that NO3NO2-N observations in the Cedar River Watershed are spatially correlated, and by ignoring the spatial correlation, the OLS method tends to over-estimate the impacts of watershed characteristics on stream NO3NO2-N concentration. In conjunction with kriging, the spatial regression method not only makes better stream NO3NO2-N concentration predictions than the OLS method, but also gives estimates of the uncertainty of the predictions, which provides useful information for optimizing the design of stream monitoring network. It is a promising tool for better managing and controlling nonpoint source pollution. ?? 2010 Elsevier Ltd.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.jenvman.2010.04.011","issn":"03014797","usgsCitation":"Yang, X., and Jin, W., 2010, GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa: Journal of Environmental Management, v. 91, no. 10, p. 1943-1951, https://doi.org/10.1016/j.jenvman.2010.04.011.","startPage":"1943","endPage":"1951","numberOfPages":"9","costCenters":[],"links":[{"id":218052,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jenvman.2010.04.011"},{"id":246032,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a146ce4b0c8380cd54a1e","contributors":{"authors":[{"text":"Yang, X.","contributorId":66894,"corporation":false,"usgs":true,"family":"Yang","given":"X.","email":"","affiliations":[],"preferred":false,"id":462200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jin, W.","contributorId":27682,"corporation":false,"usgs":true,"family":"Jin","given":"W.","email":"","affiliations":[],"preferred":false,"id":462199,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70037700,"text":"70037700 - 2010 - Evidence for a twelfth large earthquake on the southern hayward fault in the past 1900 years","interactions":[],"lastModifiedDate":"2012-04-30T16:43:33","indexId":"70037700","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for a twelfth large earthquake on the southern hayward fault in the past 1900 years","docAbstract":"We present age and stratigraphic evidence for an additional paleoearthquake at the Tyson Lagoon site. The acquisition of 19 additional radiocarbon dates and the inclusion of this additional event has resolved a large age discrepancy in our earlier earthquake chronology. The age of event E10 was previously poorly constrained, thus increasing the uncertainty in the mean recurrence interval (RI), a critical factor in seismic hazard evaluation. Reinspection of many trench logs revealed substantial evidence suggesting that an additional earthquake occurred between E10 and E9 within unit u45. Strata in older u45 are faulted in the main fault zone and overlain by scarp colluviums in two locations.We conclude that an additional surfacerupturing event (E9.5) occurred between E9 and E10. Since 91 A.D. (??40 yr, 1??), 11 paleoearthquakes preceded the M 6:8 earthquake in 1868, yielding a mean RI of 161 ?? 65 yr (1??, standard deviation of recurrence intervals). However, the standard error of the mean (SEM) is well determined at ??10 yr. Since ~1300 A.D., the mean rate has increased slightly, but is indistinguishable from the overall rate within the uncertainties. Recurrence for the 12-event sequence seems fairly regular: the coefficient of variation is 0.40, and it yields a 30-yr earthquake probability of 29%. The apparent regularity in timing implied by this earthquake chronology lends support for the use of time-dependent renewal models rather than assuming a random process to forecast earthquakes, at least for the southern Hayward fault.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1785/0120090129","issn":"00371106","usgsCitation":"Lienkaemper, J.J., Williams, P.L., and Guilderson, T., 2010, Evidence for a twelfth large earthquake on the southern hayward fault in the past 1900 years: Bulletin of the Seismological Society of America, v. 100, no. 5 A, p. 2024-2034, https://doi.org/10.1785/0120090129.","startPage":"2024","endPage":"2034","numberOfPages":"11","costCenters":[],"links":[{"id":218055,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120090129"},{"id":246035,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"5 A","noUsgsAuthors":false,"publicationDate":"2010-09-20","publicationStatus":"PW","scienceBaseUri":"505a0d33e4b0c8380cd52e8c","contributors":{"authors":[{"text":"Lienkaemper, J. J.","contributorId":71947,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"J.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":462378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, P. L.","contributorId":79109,"corporation":false,"usgs":true,"family":"Williams","given":"P.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":462379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guilderson, T.P.","contributorId":27727,"corporation":false,"usgs":true,"family":"Guilderson","given":"T.P.","affiliations":[],"preferred":false,"id":462377,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042495,"text":"70042495 - 2010 - On the resolution of shallow mantle viscosity structure using post-earthquake relaxation data: Application to the 1999 Hector Mine, California, earthquake","interactions":[],"lastModifiedDate":"2013-04-30T14:27:32","indexId":"70042495","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"On the resolution of shallow mantle viscosity structure using post-earthquake relaxation data: Application to the 1999 Hector Mine, California, earthquake","docAbstract":"Most models of lower crust/mantle viscosity inferred from postearthquake relaxation assume one or two uniform-viscosity layers. A few existing models possess apparently significant radially variable viscosity structure in the shallow mantle (e.g., the upper 200 km), but the resolution of such variations is not clear. We use a geophysical inverse procedure to address the resolving power of inferred shallow mantle viscosity structure using postearthquake relaxation data. We apply this methodology to 9 years of GPS-constrained crustal motions after the 16 October 1999 M = 7.1 Hector Mine earthquake. After application of a differencing method to isolate the postearthquake signal from the “background” crustal velocity field, we find that surface velocities diminish from ∼20 mm/yr in the first few months to ≲2 mm/yr after 2 years. Viscoelastic relaxation of the mantle, with a time-dependent effective viscosity prescribed by a Burgers body, provides a good explanation for the postseismic crustal deformation, capturing both the spatial and temporal pattern. In the context of the Burgers body model (which involves a transient viscosity and steady state viscosity), a resolution analysis based on the singular value decomposition reveals that at most, two constraints on depth-dependent steady state mantle viscosity are provided by the present data set. Uppermost mantle viscosity (depth ≲ 60 km) is moderately resolved, but deeper viscosity structure is poorly resolved. The simplest model that explains the data better than that of uniform steady state mantle viscosity involves a linear gradient in logarithmic viscosity with depth, with a small increase from the Moho to 220 km depth. However, the viscosity increase is not statistically significant. This suggests that the depth-dependent steady state viscosity is not resolvably different from uniformity in the uppermost mantle.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1029/2010JB007405","usgsCitation":"Pollitz, F., and Thatcher, W.R., 2010, On the resolution of shallow mantle viscosity structure using post-earthquake relaxation data: Application to the 1999 Hector Mine, California, earthquake: Journal of Geophysical Research B: Solid Earth, 20 p., https://doi.org/10.1029/2010JB007405.","productDescription":"20 p.","numberOfPages":"20","additionalOnlineFiles":"N","ipdsId":"IP-019815","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":271680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271679,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2010JB007405"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.56,33.01 ], [ -120.56,37.00 ], [ -114.96,37.00 ], [ -114.96,33.01 ], [ -120.56,33.01 ] ] ] } } ] }","noUsgsAuthors":false,"publicationDate":"2010-10-15","publicationStatus":"PW","scienceBaseUri":"5180e7e9e4b0df838b924d80","contributors":{"authors":[{"text":"Pollitz, Fred F. fpollitz@usgs.gov","contributorId":2408,"corporation":false,"usgs":true,"family":"Pollitz","given":"Fred F.","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":471643,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thatcher, Wayne R. 0000-0001-6324-545X thatcher@usgs.gov","orcid":"https://orcid.org/0000-0001-6324-545X","contributorId":2599,"corporation":false,"usgs":true,"family":"Thatcher","given":"Wayne","email":"thatcher@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":471644,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70036370,"text":"70036370 - 2010 - Distribution, behavior, and transport of inorganic and methylmercury in a high gradient stream","interactions":[],"lastModifiedDate":"2012-03-12T17:22:02","indexId":"70036370","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Distribution, behavior, and transport of inorganic and methylmercury in a high gradient stream","docAbstract":"Concentrations of Hg remain elevated in physical and biological media of the South River (Virginia, USA), despite the cessation of the industrial use of Hg in its watershed nearly six decades ago, and physical characteristics that would not seem to favor Hg(II)-methylation. A 3-a study of inorganic Hg (IHg) and methylmercury (MeHg) was conducted in physical media (soil, sediment, surface water, porewater and soil/sediment extracts) to identify non-point sources, transport mechanisms, and potential controls on Hg(II)-methylation. Data collected from surface water and sediment indicate that the majority of the non-point sources of IHg to the South River are within the first 14. km downstream from the historic point source. Partitioning data indicate that particle bound IHg is introduced in this reach, releasing dissolved and colloidal bound IHg, which is transported downstream. Extraction experiments revealed that floodplain soils released a higher fraction of their IHg content in aqueous extractions than fine-grained sediment (FGS). Based on ultrafiltration [<5000 nominal molecular weight cutoff (NMWC)] the majority of soil IHg released was colloidal in nature, providing evidence for the continued evolution of IHg for Hg(II)-methylation from soil. Strong seasonal patterns in MeHg concentrations were observed in surface water and sediment. The highest concentrations of MeHg in surface water were observed at moderate temperatures, suggesting that other factors limit net Hg(II)-methylation. Seasonal changes in sediment organic content and the fraction of 1. N KOH-extractable THg were also observed and may be important factors in controlling net Hg(II)-methylation rates. Sulfate concentrations in surface water are low and the evidence suggests that Fe reduction may be an important Hg(II)-methylation process. The highest sediment MeHg concentrations were observed in habitats with large amounts of FGS, which are more prevalent in the upper half of the study area due to the lower hydrologic gradient and agricultural impacts. Past and present land use practices and other geomorphologic controls contribute to the erosion of banks and accumulation of fine-grained sediment in this section of the river, acting as sources of IHg. ?? 2010 Elsevier Ltd.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.apgeochem.2010.09.004","issn":"08832927","usgsCitation":"Flanders, J., Turner, R., Morrison, T., Jensen, R., Pizzuto, J., Skalak, K., and Stahl, R., 2010, Distribution, behavior, and transport of inorganic and methylmercury in a high gradient stream: Applied Geochemistry, v. 25, no. 11, p. 1756-1769, https://doi.org/10.1016/j.apgeochem.2010.09.004.","startPage":"1756","endPage":"1769","numberOfPages":"14","costCenters":[],"links":[{"id":218581,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeochem.2010.09.004"},{"id":246606,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a031ce4b0c8380cd50346","contributors":{"authors":[{"text":"Flanders, J.R.","contributorId":87401,"corporation":false,"usgs":true,"family":"Flanders","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":455768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, R.R.","contributorId":29983,"corporation":false,"usgs":true,"family":"Turner","given":"R.R.","email":"","affiliations":[],"preferred":false,"id":455764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morrison, T.","contributorId":90966,"corporation":false,"usgs":true,"family":"Morrison","given":"T.","affiliations":[],"preferred":false,"id":455769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jensen, R.","contributorId":58877,"corporation":false,"usgs":true,"family":"Jensen","given":"R.","affiliations":[],"preferred":false,"id":455766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pizzuto, J.","contributorId":32381,"corporation":false,"usgs":true,"family":"Pizzuto","given":"J.","email":"","affiliations":[],"preferred":false,"id":455765,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skalak, K.","contributorId":22997,"corporation":false,"usgs":true,"family":"Skalak","given":"K.","affiliations":[],"preferred":false,"id":455763,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stahl, R.","contributorId":60888,"corporation":false,"usgs":true,"family":"Stahl","given":"R.","email":"","affiliations":[],"preferred":false,"id":455767,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70037027,"text":"70037027 - 2010 - Migration of northern yellowstone elk: Implications of spatial structuring","interactions":[],"lastModifiedDate":"2012-03-12T17:22:10","indexId":"70037027","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","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":"Migration of northern yellowstone elk: Implications of spatial structuring","docAbstract":"Migration can enhance survival and recruitment of mammals by increasing access to higher-quality forage or reducing predation risk, or both. We used telemetry locations collected from 140 adult female elk during 20002003 and 20072008 to identify factors influencing the migration of northern Yellowstone elk. Elk wintered in 2 semidistinct herd segments and migrated 10140 km to at least 12 summer areas in Yellowstone National Park (YNP) and nearby areas of Montana. Spring migrations were delayed after winters with increased snow pack, with earlier migration in years with earlier vegetation green-up. Elk wintering at lower elevations outside YNP migrated an average of 13 days earlier than elk at higher elevations. The timing of autumn migrations varied annually, but elk left their summer ranges at about the same time regardless of elevation, wolf numbers, or distance to their wintering areas. Elk monitored for multiple years typically returned to the same summer (96 fidelity, n 52) and winter (61 fidelity, n 41) ranges. Elk that wintered at lower elevations in or near the northwestern portion of the park tended to summer in the western part of YNP (56), and elk that wintered at higher elevations spent summer primarily in the eastern and northern parts of the park (82). Elk did not grossly modify their migration timing, routes, or use areas after wolf restoration. Elk mortality was low during summer and migration (8 of 225 elk-summers). However, spatial segregation and differential mortality and recruitment between herd segments on the northern winter range apparently contributed to a higher proportion of the elk population wintering outside the northwestern portion of YNP and summering in the western portion of the park. This change could shift wolf spatial dynamics more outside YNP and increase the risk of transmission of brucellosis from elk to cattle north of the park. ?? 2010 American Society of Mammalogists.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Mammalogy","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1644/08-MAMM-A-252.1","issn":"00222372","usgsCitation":"White, P., Proffitt, K., Mech, L., Evans, S., Cunningham, J., and Hamlin, K., 2010, Migration of northern yellowstone elk: Implications of spatial structuring: Journal of Mammalogy, v. 91, no. 4, p. 827-837, https://doi.org/10.1644/08-MAMM-A-252.1.","startPage":"827","endPage":"837","numberOfPages":"11","costCenters":[],"links":[{"id":475985,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1644/08-mamm-a-252.1","text":"Publisher Index Page"},{"id":217157,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1644/08-MAMM-A-252.1"},{"id":245078,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-08-16","publicationStatus":"PW","scienceBaseUri":"505a5709e4b0c8380cd6d9eb","contributors":{"authors":[{"text":"White, P.J.","contributorId":91436,"corporation":false,"usgs":true,"family":"White","given":"P.J.","affiliations":[],"preferred":false,"id":459037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Proffitt, K.M.","contributorId":34235,"corporation":false,"usgs":true,"family":"Proffitt","given":"K.M.","email":"","affiliations":[],"preferred":false,"id":459034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mech, L.D. 0000-0003-3944-7769","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":75466,"corporation":false,"usgs":false,"family":"Mech","given":"L.D.","email":"","affiliations":[],"preferred":false,"id":459036,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, S.B.","contributorId":19359,"corporation":false,"usgs":true,"family":"Evans","given":"S.B.","email":"","affiliations":[],"preferred":false,"id":459033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cunningham, J.A.","contributorId":101872,"corporation":false,"usgs":true,"family":"Cunningham","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":459038,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamlin, K.L.","contributorId":37174,"corporation":false,"usgs":true,"family":"Hamlin","given":"K.L.","email":"","affiliations":[],"preferred":false,"id":459035,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70037087,"text":"70037087 - 2010 - Recruitment in a Colorado population of big brown bats: Breeding probabilities, litter size, and first-year survival","interactions":[],"lastModifiedDate":"2012-03-12T17:22:11","indexId":"70037087","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","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":"Recruitment in a Colorado population of big brown bats: Breeding probabilities, litter size, and first-year survival","docAbstract":"We used markrecapture estimation techniques and radiography to test hypotheses about 3 important aspects of recruitment in big brown bats (Eptesicus fuscus) in Fort Collins, Colorado: adult breeding probabilities, litter size, and 1st-year survival of young. We marked 2,968 females with passive integrated transponder (PIT) tags at multiple sites during 2001-2005 and based our assessments on direct recaptures (breeding probabilities) and passive detection with automated PIT tag readers (1st-year survival). We interpreted our data in relation to hypotheses regarding demographic influences of bat age, roost, and effects of years with unusual environmental conditions: extreme drought (2002) and arrival of a West Nile virus epizootic (2003). Conditional breeding probabilities at 6 roosts sampled in 2002-2005 were estimated as 0.64 (95% confidence interval [95% CI] = 0.530.73) in 1-year-old females, but were consistently high (95% CI = 0.940.96) and did not vary by roost, year, or prior year breeding status in older adults. Mean litter size was 1.11 (95% CI = 1.051.17), based on examination of 112 pregnant females by radiography. Litter size was not higher in older or larger females and was similar to results of other studies in western North America despite wide variation in latitude. First-year survival was estimated as 0.67 (95% CI = 0.610.73) for weaned females at 5 maternity roosts over 5 consecutive years, was lower than adult survival (0.79; 95% CI = 0.770.81), and varied by roost. Based on model selection criteria, strong evidence exists for complex roost and year effects on 1st-year survival. First-year survival was lowest in bats born during the drought year. Juvenile females that did not return to roosts as 1-year-olds had lower body condition indices in late summer of their natal year than those known to survive. ?? 2009 American Society of Mammalogists.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Mammalogy","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1644/08-MAMM-A-295.1","issn":"00222372","usgsCitation":"O'Shea, T., Ellison, L., Neubaum, D., Neubaum, M., Reynolds, C., and Bowen, R.A., 2010, Recruitment in a Colorado population of big brown bats: Breeding probabilities, litter size, and first-year survival: Journal of Mammalogy, v. 91, no. 2, p. 418-428, https://doi.org/10.1644/08-MAMM-A-295.1.","startPage":"418","endPage":"428","numberOfPages":"11","costCenters":[],"links":[{"id":487919,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1644/08-mamm-a-295.1","text":"Publisher Index Page"},{"id":217134,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1644/08-MAMM-A-295.1"},{"id":245053,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4a353e4b0e8fec6cdb821","contributors":{"authors":[{"text":"O'Shea, T. J. 0000-0002-0758-9730","orcid":"https://orcid.org/0000-0002-0758-9730","contributorId":50100,"corporation":false,"usgs":true,"family":"O'Shea","given":"T. J.","affiliations":[],"preferred":false,"id":459313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellison, L.E.","contributorId":103610,"corporation":false,"usgs":true,"family":"Ellison","given":"L.E.","email":"","affiliations":[],"preferred":false,"id":459317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neubaum, D.J.","contributorId":43720,"corporation":false,"usgs":true,"family":"Neubaum","given":"D.J.","email":"","affiliations":[],"preferred":false,"id":459312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neubaum, M.A.","contributorId":50866,"corporation":false,"usgs":true,"family":"Neubaum","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":459314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reynolds, C.A.","contributorId":102301,"corporation":false,"usgs":true,"family":"Reynolds","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":459316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bowen, R. A.","contributorId":80623,"corporation":false,"usgs":false,"family":"Bowen","given":"R.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":459315,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70034224,"text":"70034224 - 2010 - Predicting performance for ecological restoration: A case study using Spartina altemiflora","interactions":[],"lastModifiedDate":"2012-03-12T17:21:46","indexId":"70034224","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Predicting performance for ecological restoration: A case study using Spartina altemiflora","docAbstract":"The success of population-based ecological restoration relies on the growth and reproductive performance of selected donor materials, whether consisting of whole plants or seed. Accurately predicting performance requires an understanding of a variety of underlying processes, particularly gene flow and selection, which can be measured, at least in part, using surrogates such as neutral marker genetic distances and simple latitudinal effects. Here we apply a structural equation modeling approach to understanding and predicting performance in a widespread salt marsh grass, Spartina alterniflora, commonly used for ecological restoration throughout its native range in North America. We collected source materials from throughout this range, consisting of eight clones each from 23 populations, for transplantation to a common garden site in coastal Louisiana and monitored their performance. We modeled performance as a latent process described by multiple indicator variables (e.g., clone diameter, stem number) and estimated direct and indirect influences of geographic and genetic distances on performance. Genetic distances were determined by comparison of neutral molecular markers with those from a local population at the common garden site. Geographic distance metrics included dispersal distance (the minimum distance over water between donor and experimental sites) and latitude. Model results indicate direct effects of genetic distance and latitude on performance variation among the donor sites. Standardized effect strengths indicate that performance was roughly twice as sensitive to variation in genetic distance as to latitudinal variation. Dispersal distance had an indirect influence on performance through effects on genetic distance, indicating a typical pattern of genetic isolation by distance. Latitude also had an indirect effect on genetic distance through its linear relationship with dispersal distance. Three performance indicators had significant loadings on performance alone (mean clone diameter, mean number of stems, mean number of inflorescences), while the performance indicators mean stem height and mean stem width were also influenced by latitude. We suggest that dispersal distance and latitude should provide an adequate means of predicting performance in future S. alterniflora restorations and propose a maximum sampling distance of 300 km (holding latitude constant) to avoid the sampling of inappropriate ecotypes. ?? 2010 by the Ecological Society of America.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1890/08-1443.1","issn":"10510761","usgsCitation":"Travis, S., and Grace, J., 2010, Predicting performance for ecological restoration: A case study using Spartina altemiflora: Ecological Applications, v. 20, no. 1, p. 192-204, https://doi.org/10.1890/08-1443.1.","startPage":"192","endPage":"204","numberOfPages":"13","costCenters":[],"links":[{"id":475940,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/08-1443.1","text":"Publisher Index Page"},{"id":216729,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/08-1443.1"},{"id":244615,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a81c1e4b0c8380cd7b6f1","contributors":{"authors":[{"text":"Travis, S.E. 0000-0001-9338-8953","orcid":"https://orcid.org/0000-0001-9338-8953","contributorId":28718,"corporation":false,"usgs":true,"family":"Travis","given":"S.E.","email":"","affiliations":[],"preferred":false,"id":444695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grace, J.B. 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":38938,"corporation":false,"usgs":true,"family":"Grace","given":"J.B.","affiliations":[],"preferred":false,"id":444696,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70034345,"text":"70034345 - 2010 - A geostatistical approach to mapping site response spectral amplifications","interactions":[],"lastModifiedDate":"2012-03-12T17:21:47","indexId":"70034345","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"A geostatistical approach to mapping site response spectral amplifications","docAbstract":"If quantitative estimates of the seismic properties do not exist at a location of interest then the site response spectral amplifications must be estimated from data collected at other locations. Currently, the most common approach employs correlations of site class with maps of surficial geology. Analogously, correlations of site class with topographic slope can be employed where the surficial geology is unknown. Our goal is to identify and validate a method to estimate site response with greater spatial resolution and accuracy for regions where additional effort is warranted. This method consists of three components: region-specific data collection, a spatial model for interpolating seismic properties, and a theoretical method for computing spectral amplifications from the interpolated seismic properties. We consider three spatial interpolation schemes: correlations with surficial geology, termed the geologic trend (GT), ordinary kriging (OK), and kriging with a trend (KT). We estimate the spectral amplifications from seismic properties using the square root of impedance method, thereby linking the frequency-dependent spectral amplifications to the depth-dependent seismic properties. Thus, the range of periods for which this method is applicable is limited by the depth of exploration. A dense survey of near-surface S-wave slowness (Ss) throughout Kobe, Japan shows that the geostatistical methods give more accurate estimates of Ss than the topographic slope and GT methods, and the OK and KT methods perform equally well. We prefer the KT model because it can be seamlessly integrated with geologic maps that cover larger regions. Empirical spectral amplifications show that the region-specific data achieve more accurate estimates of observed median short-period amplifications than the topographic slope method. ?? 2010 Elsevier B.V.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Engineering Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.enggeo.2010.05.010","issn":"00137952","usgsCitation":"Thompson, E., Baise, L., Kayen, R.E., Tanaka, Y., and Tanaka, H., 2010, A geostatistical approach to mapping site response spectral amplifications: Engineering Geology, v. 114, no. 3-4, p. 330-342, https://doi.org/10.1016/j.enggeo.2010.05.010.","startPage":"330","endPage":"342","numberOfPages":"13","costCenters":[],"links":[{"id":475944,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/35p167nr","text":"External Repository"},{"id":216674,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.enggeo.2010.05.010"},{"id":244559,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"114","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e407e4b0c8380cd4636b","contributors":{"authors":[{"text":"Thompson, E.M.","contributorId":104688,"corporation":false,"usgs":true,"family":"Thompson","given":"E.M.","affiliations":[],"preferred":false,"id":445334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baise, L.G.","contributorId":6239,"corporation":false,"usgs":true,"family":"Baise","given":"L.G.","affiliations":[],"preferred":false,"id":445330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kayen, R. E.","contributorId":14424,"corporation":false,"usgs":true,"family":"Kayen","given":"R.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":445332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tanaka, Y.","contributorId":14214,"corporation":false,"usgs":true,"family":"Tanaka","given":"Y.","email":"","affiliations":[],"preferred":false,"id":445331,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tanaka, H.","contributorId":35521,"corporation":false,"usgs":true,"family":"Tanaka","given":"H.","email":"","affiliations":[],"preferred":false,"id":445333,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70034225,"text":"70034225 - 2010 - The anatomy of a (potential) disaster: Volcanoes, behavior, and population viability of the short-tailed albatross (Phoebastria albatrus)","interactions":[],"lastModifiedDate":"2012-03-12T17:21:46","indexId":"70034225","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","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":"The anatomy of a (potential) disaster: Volcanoes, behavior, and population viability of the short-tailed albatross (Phoebastria albatrus)","docAbstract":"Catastrophic events, either from natural (e.g., hurricane) or human-induced (e.g., forest clear-cut) processes, are a well-known threat to wild populations. However, our lack of knowledge about population-level effects of catastrophic events has inhibited the careful examination of how catastrophes affect population growth and persistence. For the critically endangered short-tailed albatross (Phoebastria albatrus), episodic volcanic eruptions are considered a serious catastrophic threat since approximately 80% of the global population of ???2500 birds (in 2006) currently breeds on an active volcano, Torishima Island. We evaluated how short-tailed albatross population persistence is affected by the catastrophic threat of a volcanic eruption relative to chronic threats. We also provide an example for overcoming the seemingly overwhelming problems created by modelling the population dynamics of a species with limited demographic data by incorporating uncertainty in our analysis. As such, we constructed a stochastic age-based matrix model that incorporated both catastrophic mortality due to volcanic eruptions and chronic mortality from several potential sources (e.g., contaminant exposure, fisheries bycatch) to determine the relative effects of these two types of threats on short-tailed albatross population growth and persistence. Modest increases (1%) in chronic (annual) mortality had a 2.5-fold greater effect on predicted short-tailed albatross stochastic population growth rate (lambda) than did the occurrence of periodic volcanic eruptions that follow historic eruption frequencies (annual probability of eruption 2.2%). Our work demonstrates that periodic catastrophic volcanic eruptions, despite their dramatic nature, are less likely to affect the population viability and recovery of short-tailed albatross than low-level chronic mortality. ?? 2009 Elsevier Ltd.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Conservation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.biocon.2009.10.013","issn":"00063207","usgsCitation":"Finkelstein, M., Wolf, S., Goldman, M., Doak, D., Sievert, P., Balogh, G., and Hasegawa, H., 2010, The anatomy of a (potential) disaster: Volcanoes, behavior, and population viability of the short-tailed albatross (Phoebastria albatrus): Biological Conservation, v. 143, no. 2, p. 321-331, https://doi.org/10.1016/j.biocon.2009.10.013.","startPage":"321","endPage":"331","numberOfPages":"11","costCenters":[],"links":[{"id":216730,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.biocon.2009.10.013"},{"id":244616,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba9bce4b08c986b32248e","contributors":{"authors":[{"text":"Finkelstein, M.E.","contributorId":94885,"corporation":false,"usgs":true,"family":"Finkelstein","given":"M.E.","email":"","affiliations":[],"preferred":false,"id":444702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolf, S.","contributorId":76869,"corporation":false,"usgs":true,"family":"Wolf","given":"S.","affiliations":[],"preferred":false,"id":444700,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldman, M.","contributorId":84540,"corporation":false,"usgs":true,"family":"Goldman","given":"M.","affiliations":[],"preferred":false,"id":444701,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doak, D.F.","contributorId":39729,"corporation":false,"usgs":true,"family":"Doak","given":"D.F.","email":"","affiliations":[],"preferred":false,"id":444697,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sievert, P.R.","contributorId":104858,"corporation":false,"usgs":true,"family":"Sievert","given":"P.R.","email":"","affiliations":[],"preferred":false,"id":444703,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Balogh, G.","contributorId":42461,"corporation":false,"usgs":true,"family":"Balogh","given":"G.","email":"","affiliations":[],"preferred":false,"id":444698,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hasegawa, H.","contributorId":48416,"corporation":false,"usgs":true,"family":"Hasegawa","given":"H.","email":"","affiliations":[],"preferred":false,"id":444699,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70034240,"text":"70034240 - 2010 - The vegetation outlook (VegOut): a new method for predicting vegetation seasonal greenness","interactions":[],"lastModifiedDate":"2012-12-26T12:25:12","indexId":"70034240","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The vegetation outlook (VegOut): a new method for predicting vegetation seasonal greenness","docAbstract":"The vegetation outlook (VegOut) is a geospatial tool for predicting general vegetation condition patterns across large areas. VegOut predicts a standardized seasonal greenness (SSG) measure, which represents a general indicator of relative vegetation health. VegOut predicts SSG values at multiple time steps (two to six weeks into the future) based on the analysis of \"historical patterns\" (i.e., patterns at each 1 km grid cell and time of the year) of satellite, climate, and oceanic data over an 18-year period (1989 to 2006). The model underlying VegOut capitalizes on historical climate-vegetation interactions and ocean-climate teleconnections (such as El Niño and the Southern Oscillation, ENSO) expressed over the 18-year data record and also considers several environmental characteristics (e.g., land use/cover type and soils) that influence vegetation's response to weather conditions to produce 1 km maps that depict future general vegetation conditions. VegOut provides regionallevel vegetation monitoring capabilities with local-scale information (e.g., county to sub-county level) that can complement more traditional remote sensing-based approaches that monitor \"current\" vegetation conditions. In this paper, the VegOut approach is discussed and a case study over the central United States for selected periods of the 2008 growing season is presented to demonstrate the potential of this new tool for assessing and predicting vegetation conditions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"GIScience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Bellwether Publishing, Ltd.","publisherLocation":"Columbia, MD","doi":"10.2747/1548-1603.47.1.25","issn":"15481603","usgsCitation":"Tadesse, T., Wardlow, B., Hayes, M., Svoboda, M., and Brown, J., 2010, The vegetation outlook (VegOut): a new method for predicting vegetation seasonal greenness: GIScience and Remote Sensing, v. 47, no. 1, p. 25-52, https://doi.org/10.2747/1548-1603.47.1.25.","productDescription":"28 p.","startPage":"25","endPage":"52","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":475891,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2747/1548-1603.47.1.25","text":"Publisher Index Page"},{"id":244876,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":216971,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2747/1548-1603.47.1.25"}],"volume":"47","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-05-15","publicationStatus":"PW","scienceBaseUri":"505bb1b5e4b08c986b3253b6","contributors":{"authors":[{"text":"Tadesse, T.","contributorId":57661,"corporation":false,"usgs":true,"family":"Tadesse","given":"T.","affiliations":[],"preferred":false,"id":444849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wardlow, B.","contributorId":56863,"corporation":false,"usgs":false,"family":"Wardlow","given":"B.","email":"","affiliations":[{"id":12505,"text":"University of Nebraska - Lincoln","active":true,"usgs":false}],"preferred":false,"id":444848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, M.","contributorId":68138,"corporation":false,"usgs":true,"family":"Hayes","given":"M.","affiliations":[],"preferred":false,"id":444851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Svoboda, M.","contributorId":74604,"corporation":false,"usgs":true,"family":"Svoboda","given":"M.","email":"","affiliations":[],"preferred":false,"id":444852,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, J.","contributorId":57801,"corporation":false,"usgs":true,"family":"Brown","given":"J.","affiliations":[],"preferred":false,"id":444850,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037570,"text":"70037570 - 2010 - Predictions of turbidity due to enhanced sediment resuspension resulting from sea-level rise on a fringing Coral Reef: Evidence from Molokai, Hawaii","interactions":[],"lastModifiedDate":"2012-03-12T17:22:06","indexId":"70037570","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Predictions of turbidity due to enhanced sediment resuspension resulting from sea-level rise on a fringing Coral Reef: Evidence from Molokai, Hawaii","docAbstract":"Accelerating sea-level rise associated with global climate change will affect sedimentary processes on coral reefs and other shoreline environments by increasing energy and sediment resuspension. On reefs, sedimentation is known to increase coral stress and bleaching as particles that settle on coral surfaces interfere with photosynthesis and feeding, and turbidity induced by suspended sediment reduces incident light levels. Using relationships developed from observations of wave orbital velocity, water-surface elevation, and suspended-sediment concentration on a fringing reef flat of Molokai, Hawaii, predictions of the average daily maximum in suspended-sediment concentration increase from ~11 mg/l to ~20 mg/l with 20 cm sea-level rise. The duration of time concentrations exceeds 10 mg/l increases from 9 to 37. An evaluation of the reduction of wave energy flux through breaking and frictional dissipation across the reef flat shows an increase of ~80 relative to the present will potentially reach the shoreline as sea level increases by 20 cm. Where the shoreline exists on low, flat terrain, the increased energy could cause significant erosion of the shoreline. Considering the sediment budget, the sediment flux is predicted to increase and removal of fine-grained sediment may be expedited on some fringing reefs, and sediment in storage on the inner reef could ultimately be reduced. However, increased shoreline erosion may add sediment and offset removal from the reef flat. The shifts in sediment availability and transport that will occur as result of a modest increase in sea level have wide application to fringing coral reefs elsewhere, as well as other shoreline environments. ?? 2010 the Coastal Education & Research Foundation (CERF).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Coastal Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.2112/JCOASTRES-D-09-00064.1","issn":"07490208","usgsCitation":"Ogston, A., and Field, M., 2010, Predictions of turbidity due to enhanced sediment resuspension resulting from sea-level rise on a fringing Coral Reef: Evidence from Molokai, Hawaii: Journal of Coastal Research, v. 26, no. 6, p. 1027-1037, https://doi.org/10.2112/JCOASTRES-D-09-00064.1.","startPage":"1027","endPage":"1037","numberOfPages":"11","costCenters":[],"links":[{"id":246009,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218032,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2112/JCOASTRES-D-09-00064.1"}],"volume":"26","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a81fce4b0c8380cd7b836","contributors":{"authors":[{"text":"Ogston, A.S.","contributorId":86920,"corporation":false,"usgs":true,"family":"Ogston","given":"A.S.","email":"","affiliations":[],"preferred":false,"id":461667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Field, M.E.","contributorId":27052,"corporation":false,"usgs":true,"family":"Field","given":"M.E.","affiliations":[],"preferred":false,"id":461666,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70037562,"text":"70037562 - 2010 - Prey-mediated avoidance of an intraguild predator by its intraguild prey","interactions":[],"lastModifiedDate":"2012-03-12T17:22:00","indexId":"70037562","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Prey-mediated avoidance of an intraguild predator by its intraguild prey","docAbstract":"Intraguild (IG) predation is an important factor influencing community structure, yet factors allowing coexistence of IG predator and IG prey are not well understood. The existence of spatial refuges for IG prey has recently been noted for their importance in allowing coexistence. However, reduction in basal prey availability might lead IG prey to leave spatial refuges for greater access to prey, leading to increased IG predation and fewer opportunities for coexistence. We determined how the availability of prey affected space-use patterns of bobcats (Lynx rufus, IG prey) in relation to coyote space-use patterns (Canis latrans, IG predators). We located animals from fall 2007 to spring 2009 and estimated bobcat home ranges and core areas seasonally. For each bobcat relocation, we determined intensity of coyote use, distance to water, small mammal biomass, and mean small mammal biomass of the home range during the season the location was collected. We built generalized linear mixed models and used Akaike Information Criteria to determine which factors best predicted bobcat space use. Coyote intensity was a primary determinant of bobcat core area location. In bobcat home ranges with abundant prey, core areas occurred where coyote use was low, but shifted to areas intensively used by coyotes when prey declined. High spatial variability in basal prey abundance allowed some bobcats to avoid coyotes while at the same time others were forced into more risky areas. Our results suggest that multiple behavioral strategies associated with spatial variation in basal prey abundance likely allow IG prey and IG predators to coexist. ?? 2010 Springer-Verlag.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Oecologia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1007/s00442-010-1797-8","issn":"00298549","usgsCitation":"Wilson, R., Blankenship, T., Hooten, M., and Shivik, J., 2010, Prey-mediated avoidance of an intraguild predator by its intraguild prey: Oecologia, v. 164, no. 4, p. 921-929, https://doi.org/10.1007/s00442-010-1797-8.","startPage":"921","endPage":"929","numberOfPages":"9","costCenters":[],"links":[{"id":217972,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00442-010-1797-8"},{"id":245945,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"164","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-10-16","publicationStatus":"PW","scienceBaseUri":"505a8b87e4b0c8380cd7e28f","contributors":{"authors":[{"text":"Wilson, R.R.","contributorId":12138,"corporation":false,"usgs":true,"family":"Wilson","given":"R.R.","email":"","affiliations":[],"preferred":false,"id":461605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blankenship, T.L.","contributorId":66103,"corporation":false,"usgs":true,"family":"Blankenship","given":"T.L.","email":"","affiliations":[],"preferred":false,"id":461608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, M.B.","contributorId":50261,"corporation":false,"usgs":true,"family":"Hooten","given":"M.B.","email":"","affiliations":[],"preferred":false,"id":461606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shivik, J.A.","contributorId":58500,"corporation":false,"usgs":true,"family":"Shivik","given":"J.A.","affiliations":[],"preferred":false,"id":461607,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70037559,"text":"70037559 - 2010 - Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon","interactions":[],"lastModifiedDate":"2012-03-12T17:22:01","indexId":"70037559","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1574,"text":"Environmental & Engineering Geoscience","printIssn":"1078-7275","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon","docAbstract":"We examined elevation changes detected from two successive sets of Light Detection and Ranging (LiDAR) data in the northern Coast Range of Oregon. The first set of LiDAR data was acquired during leafon conditions and the second set during leaf-off conditions. We were able to successfully identify and map active landslides using a differential digital elevation model (DEM) created from the two LiDAR data sets, but this required the use of thresholds (0.50 and 0.75 m) to remove noise from the differential elevation data, visual pattern recognition of landslideinduced elevation changes, and supplemental QuickBird satellite imagery. After mapping, we field-verified 88 percent of the landslides that we had mapped with high confidence, but we could not detect active landslides with elevation changes of less than 0.50 m. Volumetric calculations showed that a total of about 18,100 m3 of material was missing from landslide areas, probably as a result of systematic negative elevation errors in the differential DEM and as a result of removal of material by erosion and transport. We also examined the accuracies of 285 leaf-off LiDAR elevations at four landslide sites using Global Positioning System and total station surveys. A comparison of LiDAR and survey data indicated an overall root mean square error of 0.50 m, a maximum error of 2.21 m, and a systematic error of 0.09 m. LiDAR ground-point densities were lowest in areas with young conifer forests and deciduous vegetation, which resulted in extensive interpolations of elevations in the leaf-on, bare-earth DEM. For optimal use of multi-temporal LiDAR data in forested areas, we recommend that all data sets be flown during leaf-off seasons.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental and Engineering Geoscience","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.2113/gseegeosci.16.4.315","issn":"10787275","usgsCitation":"Burns, W., Coe, J.A., Kaya, B., and Ma, L., 2010, Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon: Environmental & Engineering Geoscience, v. 16, no. 4, p. 315-341, https://doi.org/10.2113/gseegeosci.16.4.315.","startPage":"315","endPage":"341","numberOfPages":"27","costCenters":[],"links":[{"id":245919,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217946,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2113/gseegeosci.16.4.315"}],"volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-10-26","publicationStatus":"PW","scienceBaseUri":"5059eb11e4b0c8380cd48bc5","contributors":{"authors":[{"text":"Burns, W.J.","contributorId":32019,"corporation":false,"usgs":true,"family":"Burns","given":"W.J.","email":"","affiliations":[],"preferred":false,"id":461599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coe, J. A.","contributorId":8867,"corporation":false,"usgs":true,"family":"Coe","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":461597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaya, B.S.","contributorId":100226,"corporation":false,"usgs":true,"family":"Kaya","given":"B.S.","email":"","affiliations":[],"preferred":false,"id":461600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ma, Liwang","contributorId":29140,"corporation":false,"usgs":true,"family":"Ma","given":"Liwang","email":"","affiliations":[],"preferred":false,"id":461598,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70037555,"text":"70037555 - 2010 - Response to Germann's \"Comment on 'theory for source-responsive and free-surface film modeling of unsaturated flow'\"","interactions":[],"lastModifiedDate":"2018-01-12T17:37:37","indexId":"70037555","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Response to Germann's \"Comment on 'theory for source-responsive and free-surface film modeling of unsaturated flow'\"","docAbstract":"Germann's (2010) comment helpfully presents supporting evidence that I have missed, notes items that need clarification or correction, and stimulates discussion of what is needed for improved theory of unsaturated flow. Several points from this comment relate not only to specific features of the content of my paper (Nimmo, 2010), but also to the broader question of what methodology is appropriate for developing an applied earth science. Accordingly, before addressing specific points that Germann identified, I present here some considerations of purpose and background relevant to evaluation of the unsaturated flow model of Nimmo (2010).
","language":"English","publisher":"ACSESS","doi":"10.2136/vzj2010.0088","usgsCitation":"Nimmo, J., 2010, Response to Germann's \"Comment on 'theory for source-responsive and free-surface film modeling of unsaturated flow'\": Vadose Zone Journal, v. 9, no. 4, p. 1102-1104, https://doi.org/10.2136/vzj2010.0088.","productDescription":"3 p.","startPage":"1102","endPage":"1104","costCenters":[],"links":[{"id":245905,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505aaa87e4b0c8380cd863a4","contributors":{"authors":[{"text":"Nimmo, J. R. 0000-0001-8191-1727","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":58304,"corporation":false,"usgs":true,"family":"Nimmo","given":"J. 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The source data set is Saturation Overland Flow Estimated by TOPMODEL for the Conterminous United States (Wolock, 2003). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49124","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Saturation Excess-Overland Flow, 2002: U.S. Geological Survey Data Series 491-24, Dataset, https://doi.org/10.3133/dds49124.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274407,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_satof.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d2a4e1e4b0ca18483389d8","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480176,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046754,"text":"dds49123 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Mean Annual R-factor, 1971-2000","interactions":[],"lastModifiedDate":"2013-11-25T16:08:46","indexId":"dds49123","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"491-23","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Mean Annual R-factor, 1971-2000","docAbstract":"This tabular data set represents the average annual R-factor, rainfall-runoff erosivity measure, compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data are from Christopher Daly of the Spatial Climate Analysis Service, Oregon State University, and George Taylor of the Oregon Climate Service, Oregon State University (2002). The ERF1_2 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49123","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Mean Annual R-factor, 1971-2000: U.S. Geological Survey Data Series 491-23, Dataset, https://doi.org/10.3133/dds49123.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274401,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_rfact30.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d2a4e3e4b0ca18483389f3","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480166,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046753,"text":"dds49122 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Estimated Mean Annual Natural Groundwater Recharge, 2002","interactions":[],"lastModifiedDate":"2013-11-25T16:08:13","indexId":"dds49122","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"491-22","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Estimated Mean Annual Natural Groundwater Recharge, 2002","docAbstract":"This tabular data set represents the mean annual natural groundwater recharge, in millimeters, compiled for every MRB_E2RF1catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data set is Estimated Mean Annual Natural Ground-Water Recharge in the Conterminous United States (Wolock, 2003). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49122","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Estimated Mean Annual Natural Groundwater Recharge, 2002: U.S. Geological Survey Data Series 491-22, Dataset, https://doi.org/10.3133/dds49122.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274387,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_recharge.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d2a4e2e4b0ca18483389e3","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480164,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046752,"text":"dds49121 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: 30-Year Average Annual Precipitation, 1971-2000","interactions":[],"lastModifiedDate":"2013-11-25T16:04:42","indexId":"dds49121","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"491-21","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: 30-Year Average Annual Precipitation, 1971-2000","docAbstract":"This tabular data set represents the 30-year (1971-2000) average annual precipitation in millimeters multiplied by 100 compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data were the United States Average Monthly or Annual Minimum Precipitation, 1971 - 2000 raster data set produced by the PRISM Group at Oregon State University. The MRB_E2RF1 catchments are based on a modified version of the Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; J.W. Brakebill, U.S. Geological Survey, written commun., 2008). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49121","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: 30-Year Average Annual Precipitation, 1971-2000: U.S. Geological Survey Data Series 491-21, Dataset, https://doi.org/10.3133/dds49121.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274384,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_ppt30yr.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d2a4e1e4b0ca18483389d4","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480162,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}