{"pageNumber":"817","pageRowStart":"20400","pageSize":"25","recordCount":40767,"records":[{"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":70037051,"text":"70037051 - 2010 - Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification","interactions":[],"lastModifiedDate":"2012-03-12T17:22:10","indexId":"70037051","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1039,"text":"Biometrics","active":true,"publicationSubtype":{"id":10}},"title":"Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification","docAbstract":"Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f = A???x of a latent multinomial variable x with cell probability vector ?? = ??(??). Given that full conditional distributions [?? | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, ??], which is made possible by knowledge of the null space of A???. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks. ?? 2009, The International Biometric Society.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biometrics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1111/j.1541-0420.2009.01244.x","issn":"0006341X","usgsCitation":"Link, W., Yoshizaki, J., Bailey, L., and Pollock, K.H., 2010, Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification: Biometrics, v. 66, no. 1, p. 178-185, https://doi.org/10.1111/j.1541-0420.2009.01244.x.","startPage":"178","endPage":"185","numberOfPages":"8","costCenters":[],"links":[{"id":475979,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1541-0420.2009.01244.x","text":"Publisher Index Page"},{"id":217074,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1541-0420.2009.01244.x"},{"id":244986,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"1","noUsgsAuthors":false,"publicationDate":"2010-03-17","publicationStatus":"PW","scienceBaseUri":"505bbc31e4b08c986b328ac5","contributors":{"authors":[{"text":"Link, W.A. 0000-0002-9913-0256","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":8815,"corporation":false,"usgs":true,"family":"Link","given":"W.A.","affiliations":[],"preferred":false,"id":459153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yoshizaki, J.","contributorId":79596,"corporation":false,"usgs":true,"family":"Yoshizaki","given":"J.","email":"","affiliations":[],"preferred":false,"id":459156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bailey, L.L. 0000-0002-5959-2018","orcid":"https://orcid.org/0000-0002-5959-2018","contributorId":61006,"corporation":false,"usgs":true,"family":"Bailey","given":"L.L.","affiliations":[],"preferred":false,"id":459154,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pollock, K. H.","contributorId":65184,"corporation":false,"usgs":false,"family":"Pollock","given":"K.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":459155,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70037643,"text":"70037643 - 2010 - Climate change threatens polar bear populations: A stochastic demographic analysis","interactions":[],"lastModifiedDate":"2012-03-12T17:22:07","indexId":"70037643","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Climate change threatens polar bear populations: A stochastic demographic analysis","docAbstract":"The polar bear (Ursus maritimus) depends on sea ice for feeding, breeding, and movement. Significant reductions in Arctic sea ice are forecast to continue because of climate warming. We evaluated the impacts of climate change on polar bears in the southern Beaufort Sea by means of a demographic analysis, combining deterministic, stochastic, environment-dependent matrix population models with forecasts of future sea ice conditions from IPCC general circulation models (GCMs). The matrix population models classified individuals by age and breeding status; mothers and dependent cubs were treated as units. Parameter estimates were obtained from a capture-recapture study conducted from 2001 to 2006. Candidate statistical models allowed vital rates to vary with time and as functions of a sea ice covariate. Model averaging was used to produce the vital rate estimates, and a parametric bootstrap procedure was used to quantify model selection and parameter estimation uncertainty. Deterministic models projected population growth in years with more extensive ice coverage (2001-2003) and population decline in years with less ice coverage (2004-2005). LTRE (life table response experiment) analysis showed that the reduction in ?? in years with low sea ice was due primarily to reduced adult female survival, and secondarily to reduced breeding. A stochastic model with two environmental states, good and poor sea ice conditions, projected a declining stochastic growth rate, log ??s, as the frequency of poor ice years increased. The observed frequency of poor ice years since 1979 would imply log ??s ' - 0.01, which agrees with available (albeit crude) observations of population size. The stochastic model was linked to a set of 10 GCMs compiled by the IPCC; the models were chosen for their ability to reproduce historical observations of sea ice and were forced with \"business as usual\" (A1B) greenhouse gas emissions. The resulting stochastic population projections showed drastic declines in the polar bear population by the end of the 21st century. These projections were instrumental in the decision to list the polar bear as a threatened species under the U.S. Endangered Species Act. ?? 2010 by the Ecological Society of America.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1890/09-1641.1","issn":"00129658","usgsCitation":"Hunter, C., Caswell, H., Runge, M., Regehr, E., Amstrup, S.C., and Stirling, I., 2010, Climate change threatens polar bear populations: A stochastic demographic analysis: Ecology, v. 91, no. 10, p. 2883-2897, https://doi.org/10.1890/09-1641.1.","startPage":"2883","endPage":"2897","numberOfPages":"15","costCenters":[],"links":[{"id":475790,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/09-1641.1","text":"Publisher Index Page"},{"id":218103,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/09-1641.1"},{"id":246085,"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":"5059f64ee4b0c8380cd4c69a","contributors":{"authors":[{"text":"Hunter, C.M.","contributorId":19670,"corporation":false,"usgs":true,"family":"Hunter","given":"C.M.","email":"","affiliations":[],"preferred":false,"id":462065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caswell, H.","contributorId":103114,"corporation":false,"usgs":true,"family":"Caswell","given":"H.","email":"","affiliations":[],"preferred":false,"id":462069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runge, M.C. 0000-0002-8081-536X","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":49312,"corporation":false,"usgs":true,"family":"Runge","given":"M.C.","affiliations":[],"preferred":false,"id":462066,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Regehr, E.V.","contributorId":90937,"corporation":false,"usgs":true,"family":"Regehr","given":"E.V.","affiliations":[],"preferred":false,"id":462068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amstrup, Steven C.","contributorId":67034,"corporation":false,"usgs":false,"family":"Amstrup","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":13182,"text":"Polar Bears International","active":true,"usgs":false}],"preferred":false,"id":462067,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stirling, I.","contributorId":103615,"corporation":false,"usgs":false,"family":"Stirling","given":"I.","email":"","affiliations":[],"preferred":false,"id":462070,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70043220,"text":"70043220 - 2010 - Using the Sonoran and Libyan Desert test sites to monitor the temporal stability of reflective solar bands for Landsat 7 enhanced thematic mapper plus and Terra moderate resolution imaging spectroradiometer sensors","interactions":[],"lastModifiedDate":"2013-05-15T12:29:32","indexId":"70043220","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2172,"text":"Journal of Applied Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Using the Sonoran and Libyan Desert test sites to monitor the temporal stability of reflective solar bands for Landsat 7 enhanced thematic mapper plus and Terra moderate resolution imaging spectroradiometer sensors","docAbstract":"Remote sensing imagery is effective for monitoring environmental and climatic changes because of the extent of the global coverage and long time scale of the observations. Radiometric calibration of remote sensing sensors is essential for quantitative & qualitative science and applications. Pseudo-invariant ground targets have been extensively used to monitor the long-term radiometric calibration stability of remote sensing sensors. This paper focuses on the use of the Sonoran Desert site to monitor the radiometric stability of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The results are compared with the widely used Libya 4 Desert site in an attempt to evaluate the suitability of the Sonoran Desert site for sensor inter-comparison and calibration stability monitoring. Since the overpass times of ETM+ and MODIS differ by about 30 minutes, the impacts due to different view geometries or test site Bi-directional Reflectance Distribution Function (BRDF) are also presented. In general, the long-term drifts in the visible bands are relatively large compared to the drift in the near-infrared bands of both sensors. The lifetime Top-of-Atmosphere (TOA) reflectance trends from both sensors over 10 years are extremely stable, changing by no more than 0.1% per year (except ETM+ Band 1 and MODIS Band 3) over the two sites used for the study. The use of a semi-empirical BRDF model can reduce the impacts due to view geometries, thus enabling a better estimate of sensor temporal drifts.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SPIE Digital Library","doi":"10.1117/1.3424910","usgsCitation":"Angal, A., Xiong, X., Choi, T., Chander, G., and Wu, A., 2010, Using the Sonoran and Libyan Desert test sites to monitor the temporal stability of reflective solar bands for Landsat 7 enhanced thematic mapper plus and Terra moderate resolution imaging spectroradiometer sensors: Journal of Applied Remote Sensing, v. 4, no. 1, 043525, https://doi.org/10.1117/1.3424910.","productDescription":"043525","ipdsId":"IP-016646","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272292,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1117/1.3424910"}],"country":"United States","volume":"4","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51955850e4b0a933d82c4ccf","contributors":{"authors":[{"text":"Angal, Amit","contributorId":67394,"corporation":false,"usgs":true,"family":"Angal","given":"Amit","email":"","affiliations":[],"preferred":false,"id":473192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xiong, Xiaoxiong","contributorId":15088,"corporation":false,"usgs":true,"family":"Xiong","given":"Xiaoxiong","email":"","affiliations":[],"preferred":false,"id":473190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choi, Tae-young","contributorId":89036,"corporation":false,"usgs":true,"family":"Choi","given":"Tae-young","affiliations":[],"preferred":false,"id":473193,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":473189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wu, Aisheng","contributorId":65362,"corporation":false,"usgs":true,"family":"Wu","given":"Aisheng","email":"","affiliations":[],"preferred":false,"id":473191,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70037651,"text":"70037651 - 2010 - A general science-based framework for dynamical spatio-temporal models","interactions":[],"lastModifiedDate":"2012-04-30T16:43:35","indexId":"70037651","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3533,"text":"Test","active":true,"publicationSubtype":{"id":10}},"title":"A general science-based framework for dynamical spatio-temporal models","docAbstract":"Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic nonlinearity and demonstrate that it accommodates many different classes of scientific-based parameterizations as special cases. The model is presented in a hierarchical Bayesian framework and is illustrated with examples from ecology and oceanography. ?? 2010 Sociedad de Estad??stica e Investigaci??n Operativa.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Test","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1007/s11749-010-0209-z","issn":"11330686","usgsCitation":"Wikle, C.K., and Hooten, M., 2010, A general science-based framework for dynamical spatio-temporal models: Test, v. 19, no. 3, p. 417-451, https://doi.org/10.1007/s11749-010-0209-z.","startPage":"417","endPage":"451","numberOfPages":"35","costCenters":[],"links":[{"id":217926,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11749-010-0209-z"},{"id":245899,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"3","noUsgsAuthors":false,"publicationDate":"2010-11-03","publicationStatus":"PW","scienceBaseUri":"5059e3ede4b0c8380cd462d9","contributors":{"authors":[{"text":"Wikle, C. K.","contributorId":57975,"corporation":false,"usgs":true,"family":"Wikle","given":"C.","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":462110,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, M.B.","contributorId":50261,"corporation":false,"usgs":true,"family":"Hooten","given":"M.B.","email":"","affiliations":[],"preferred":false,"id":462109,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70044481,"text":"70044481 - 2010 - Mid-Piacensian mean annual sea surface temperature: an analysis for data-model comparisons","interactions":[],"lastModifiedDate":"2013-04-30T11:18:00","indexId":"70044481","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Mid-Piacensian mean annual sea surface temperature: an analysis for data-model comparisons","docAbstract":"Numerical models of the global climate system are the primary tools used to understand and project climate disruptions in the form of future global warming. The Pliocene has been identified as the closest, albeit imperfect, analog to climate conditions expected for the end of this century, making an independent data set of Pliocene conditions necessary for ground truthing model results. Because most climate model output is produced in the form ofmean annual conditions, we present a derivative of the USGS PRISM3 Global Climate Reconstruction which integrates multiple proxies of sea surface temperature (SST) into single surface temperature anomalies. We analyze temperature estimates from faunal and floral assemblage data,Mg/Ca values and alkenone unsaturation indices to arrive at a single mean annual SST anomaly (Pliocene minus modern) best describing each PRISM site, understanding that multiple proxies should not necessarily show concordance. The power of themultiple proxy approach lies within its diversity, as no two proxies measure the same environmental variable. This data set can be used to verify climate model output, to serve as a starting point for model inter-comparisons, and for quantifying uncertainty in Pliocene model prediction in perturbed physics ensembles.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Stratigraphy","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Micropaleontology Press","usgsCitation":"Dowsett, H.J., Robinson, M.M., Foley, K.M., and Stoll, D.K., 2010, Mid-Piacensian mean annual sea surface temperature: an analysis for data-model comparisons: Stratigraphy, v. 7, no. 2-3, p. 189-198.","productDescription":"10 p.","startPage":"189","endPage":"198","additionalOnlineFiles":"N","ipdsId":"IP-025169","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":271645,"type":{"id":11,"text":"Document"},"url":"https://www.micropress.org/micropen2/articles/1/6/16999_articles_article_file_1696.pdf"},{"id":271646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5180e7e7e4b0df838b924d6e","contributors":{"authors":[{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":475699,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Marci M. 0000-0002-9200-4097 mmrobinson@usgs.gov","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":2082,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci","email":"mmrobinson@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":475700,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":475701,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stoll, Danielle K.","contributorId":88236,"corporation":false,"usgs":true,"family":"Stoll","given":"Danielle","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":475702,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70037579,"text":"70037579 - 2010 - Assessment of undiscovered conventional oil and gas resources, onshore Claiborne Group, United Statespart of the northern Gulf of Mexico Basin","interactions":[],"lastModifiedDate":"2013-01-16T20:17:25","indexId":"70037579","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":701,"text":"American Association of Petroleum Geologists Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of undiscovered conventional oil and gas resources, onshore Claiborne Group, United Statespart of the northern Gulf of Mexico Basin","docAbstract":"The middle Eocene Claiborne Group was assessed for undiscovered conventional hydrocarbon resources using established U.S. Geological Survey assessment methodology. This work was conducted as part of a 2007 assessment of Paleogene-Neogene strata of the northern Gulf of Mexico Basin, including the United States onshore and state waters (Dubiel et al., 2007). The assessed area is within the Upper Jurassic-CretaceousTertiary composite total petroleum system, which was defined for the assessment. Source rocks for Claiborne oil accumulations are interpreted to be organic-rich, downdip, shaley facies of the Wilcox Group and the Sparta Sand of the Claiborne Group; gas accumulations may have originated from multiple sources, including the Jurassic Smackover Formation and the Haynesville and Bossier shales, the Cretaceous Eagle Ford and Pearsall (?) formations, and the Paleogene Wilcox Group and Sparta Sand. Hydrocarbon generation in the basin started prior to deposition of Claiborne sediments and is currently ongoing. Primary reservoir sandstones in the Claiborne Group include, from oldest to youngest, the Queen City Sand, Cook Mountain Formation, Sparta Sand, Yegua Formation, and the laterally equivalent Cockfield Formation. A geologic model, supported by spatial analysis of petroleum geology data, including discovered reservoir depths, thicknesses, temperatures, porosities, permeabilities, and pressures, was used to divide the Claiborne Group into seven assessment units (AUs) with three distinctive structural and depositional settings. The three structural and depositional settings are (1) stable shelf, (2) expanded fault zone, and (3) slope and basin floor; the seven AUs are (1) lower Claiborne stable-shelf gas and oil, (2) lower Claiborne expanded fault-zone gas, (3) lower Claiborne slope and basin-floor gas, (4) lower Claiborne Cane River, (5) upper Claiborne stable-shelf gas and oil, (6) upper Claiborne expanded fault-zone gas, and (7) upper Claiborne slope and basin-floor gas. Based on Monte Carlo simulation of justified input parameters, the total estimated mean undiscovered conventional hydrocarbon resources in the seven AUs combined are 52 million bbl of oil, 19.145 tcf of natural gas, and 1.205 billion bbl of natural gas liquids. This article describes the conceptual geologic model used to define the seven Claiborne AUs, the characteristics of each AU, and the justification behind the input parameters used to estimate undiscovered resources for each AU. The great bulk of undiscovered hydrocarbon resources are predicted to be nonassociated gas and natural gas liquids contained in deep (mostiy >12,000-ft [3658 m], present-day drilling depths), overpressured, structurally complex outer shelf or slope and basin-floor Claiborne reservoirs. The continuing development of these downdip objectives is expected to be the primary focus of exploration activity for the onshore middle Eocene Gulf Coast in the coming decades. ?? 2010 U.S. Geological Survey. All rights reserved.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"American Association of Petroleum Geologists Bulletin","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Association of Petroleum Geologists (AAPG)","publisherLocation":"Tulsa, OK","doi":"10.1306/04061009139","issn":"01491423","usgsCitation":"Hackley, P., and Ewing, T., 2010, Assessment of undiscovered conventional oil and gas resources, onshore Claiborne Group, United Statespart of the northern Gulf of Mexico Basin: American Association of Petroleum Geologists Bulletin, v. 94, no. 10, p. 1607-1636, https://doi.org/10.1306/04061009139.","startPage":"1607","endPage":"1636","numberOfPages":"30","costCenters":[],"links":[{"id":246070,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218089,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1306/04061009139"}],"volume":"94","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ee6ee4b0c8380cd49d61","contributors":{"authors":[{"text":"Hackley, P.C. 0000-0002-5957-2551","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":60756,"corporation":false,"usgs":true,"family":"Hackley","given":"P.C.","affiliations":[],"preferred":false,"id":461733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ewing, T.E.","contributorId":34369,"corporation":false,"usgs":true,"family":"Ewing","given":"T.E.","email":"","affiliations":[],"preferred":false,"id":461732,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70036507,"text":"70036507 - 2010 - Reserve growth in oil pools of Alberta: Model and forecast","interactions":[],"lastModifiedDate":"2012-03-12T17:22:05","indexId":"70036507","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1100,"text":"Bulletin of Canadian Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Reserve growth in oil pools of Alberta: Model and forecast","docAbstract":"Reserve growth is recognized as a major component of additions to reserves in most oil provinces around the world, particularly in mature provinces. It takes place as a result of the discovery of new pools/reservoirs and extensions of known pools within existing fields, improved knowledge of reservoirs over time leading to a change in estimates of original oil-in-place, and improvement in recovery factor through the application of new technology, such as enhanced oil recovery methods, horizontal/multilateral drilling, and 4D seismic. A reserve growth study was conducted on oil pools in Alberta, Canada, with the following objectives: 1) evaluate historical oil reserve data in order to assess the potential for future reserve growth; 2) develop reserve growth models/ functions to help forecast hydrocarbon volumes; 3) study reserve growth sensitivity to various parameters (for example, pool size, porosity, and oil gravity); and 4) compare reserve growth in oil pools and fields in Alberta with those from other large petroleum provinces around the world. The reported known recoverable oil exclusive of Athabasca oil sands in Alberta increased from 4.5 billion barrels of oil (BBO) in 1960 to 17 BBO in 2005. Some of the pools that were included in the existing database were excluded from the present study for lack of adequate data. Therefore, the known recoverable oil increased from 4.2 to 13.9 BBO over the period from 1960 through 2005, with new discoveries contributing 3.7 BBO and reserve growth adding 6 BBO. This reserve growth took place mostly in pools with more than 125,000 barrels of known recoverable oil. Pools with light oil accounted for most of the total known oil volume, therefore reflecting the overall pool growth. Smaller pools, in contrast, shrank in their total recoverable volumes over the years. Pools with heavy oil (gravity less than 20o API) make up only a small share (3.8 percent) of the total recoverable oil; they showed a 23-fold growth compared to about 3.5-fold growth in pools with medium oil and 2.2-fold growth in pools with light oil over a fifty-year period. The analysis indicates that pools with high porosity reservoirs (greater than 30 percent porosity) grew more than pools with lower porosity reservoirs which could possibly be attributed to permeability differences between the two types. Reserve growth models for Alberta, Canada, show the growth at field level is almost twice as much as at pool level, possibly because the analysis has evaluated fields with two or more pools with different discovery years. Based on the models, the growth in oil volumes in Alberta pools over the next five-year period (2006-2010) is expected to be about 454 million barrels of oil. Over a twenty-five year period, the cumulative reserve growth in Alberta oil pools has been only 2-fold compared to a 4- to- 5-fold increase in other petroleum producing areas such as Saskatchewan, Volga-Ural, U.S. onshore fields, and U.S. Gulf of Mexico. However, the growth at the field level compares well with that of U.S. onshore fields. In other petroleum provinces, the reserves are reported at field levels rather than at pool levels, the latter basically being the equivalent of individual reservoirs. ?? 2010 by the Canadian Society of Petroleum Geologists.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of Canadian Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.2113/gscpgbull.58.3.283","issn":"00074802","usgsCitation":"Verma, M., and Cook, T., 2010, Reserve growth in oil pools of Alberta: Model and forecast: Bulletin of Canadian Petroleum Geology, v. 58, no. 3, p. 283-293, https://doi.org/10.2113/gscpgbull.58.3.283.","startPage":"283","endPage":"293","numberOfPages":"11","costCenters":[],"links":[{"id":218209,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2113/gscpgbull.58.3.283"},{"id":246196,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-01-24","publicationStatus":"PW","scienceBaseUri":"505aa94ce4b0c8380cd85d1b","contributors":{"authors":[{"text":"Verma, M.","contributorId":72237,"corporation":false,"usgs":true,"family":"Verma","given":"M.","email":"","affiliations":[],"preferred":false,"id":456475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, T.","contributorId":59991,"corporation":false,"usgs":true,"family":"Cook","given":"T.","affiliations":[],"preferred":false,"id":456474,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046765,"text":"70046765 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Normalized Atmospheric Deposition for 2002, Total Inorganic Nitrogen","interactions":[],"lastModifiedDate":"2013-11-25T16:07:18","indexId":"70046765","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":"491-27","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Normalized Atmospheric Deposition for 2002, Total Inorganic Nitrogen","docAbstract":"This tabular data set represents the average normalized atmospheric (wet) deposition, in kilograms per square kilometer multiplied by 100, of Total Inorganic Nitrogen for the year 2002 compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). Estimates of Total Inorganic Nitrogen deposition are based on National Atmospheric Deposition Program (NADP) measurements (B. Larsen, U.S. Geological Survey, written. commun., 2007). De-trending methods applied to the year 2002 are described in Alexander and others, 2001. NADP site selection met the following criteria: stations must have records from 1995 to 2002 and have a minimum of 30 observations. 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":"10.3133/70046765","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Normalized Atmospheric Deposition for 2002, Total Inorganic Nitrogen: U.S. Geological Survey Data Series 491-27, Dataset, https://doi.org/10.3133/70046765.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274431,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_tin.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":"51d3f663e4b09630fbdc5279","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":480190,"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":480191,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70037644,"text":"70037644 - 2010 - Constructing an interdisciplinary flow regime recommendation","interactions":[],"lastModifiedDate":"2012-03-12T17:22:07","indexId":"70037644","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Constructing an interdisciplinary flow regime recommendation","docAbstract":"It is generally agreed that river rehabilitation most often relies on restoring a more natural flow regime, but credibly defining the desired regime can be problematic. I combined four distinct methods to develop and refine month-by-month and event-based flow recommendations to protect and partially restore the ecological integrity of the Cache la Poudre River through Fort Collins, Colorado. A statistical hydrologic approach was used to summarize the river's natural flow regime and set provisional monthly flow targets at levels that were historically exceeded 75% of the time. These preliminary monthly targets were supplemented using results from three Poudre-specific disciplinary studies. A substrate maintenance flow model was used to better define the high flows needed to flush accumulated sediment from the river's channel and help sustain the riparian zone in this snowmelt-dominated river. A hydraulic/habitat model and a water temperature model were both used to better define the minimum flows necessary to maintain a thriving cool water fishery. The result is a range of recommended monthly flows and daily flow guidance illustrating the advantage of combining a wide range of available disciplinary information, supplemented by judgment based on ecological principles and a general understanding of river ecosystems, in a highly altered, working river. ?? 2010 American Water Resources Association.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of the American Water Resources Association","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1111/j.1752-1688.2010.00461.x","issn":"1093474X","usgsCitation":"Bartholow, J., 2010, Constructing an interdisciplinary flow regime recommendation: Journal of the American Water Resources Association, v. 46, no. 5, p. 892-906, https://doi.org/10.1111/j.1752-1688.2010.00461.x.","startPage":"892","endPage":"906","numberOfPages":"15","costCenters":[],"links":[{"id":218104,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1752-1688.2010.00461.x"},{"id":246086,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"5","noUsgsAuthors":false,"publicationDate":"2010-07-26","publicationStatus":"PW","scienceBaseUri":"5059fa12e4b0c8380cd4d90e","contributors":{"authors":[{"text":"Bartholow, J.M.","contributorId":54530,"corporation":false,"usgs":true,"family":"Bartholow","given":"J.M.","email":"","affiliations":[],"preferred":false,"id":462071,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046736,"text":"dds49114 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Normalized Atmospheric Deposition for 2002, Ammonium (NH4)","interactions":[],"lastModifiedDate":"2013-11-25T16:07:48","indexId":"dds49114","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":"491-14","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Normalized Atmospheric Deposition for 2002, Ammonium (NH4)","docAbstract":"This tabular data set represents the average normalized (wet) deposition, in kilograms per square kilometer multiplied by 100, of ammonium (NH4) for the year 2002 compiled for every MRB_E2RF1 catchment of the Major River Basins (MRBs, Crawford and others, 2006). Estimates of NH4 deposition are based on National Atmospheric Deposition Program (NADP) measurements (B. Larsen, U.S. Geological Survey, written. commun., 2007). De-trending methods applied to the year 2002 are described in Alexander and others, 2001. NADP site selection met the following criteria: stations must have records from 1995 to 2002 and have a minimum of 30 observations. 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/dds49114","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Normalized Atmospheric Deposition for 2002, Ammonium (NH4): U.S. Geological Survey Data Series 491-14, Dataset, https://doi.org/10.3133/dds49114.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274363,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_nh4.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":"51d2a4e4e4b0ca1848338a07","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":480137,"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":480138,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70037622,"text":"70037622 - 2010 - Allocating monitoring effort in the face of unknown unknowns","interactions":[],"lastModifiedDate":"2012-03-12T17:22:01","indexId":"70037622","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Allocating monitoring effort in the face of unknown unknowns","docAbstract":"There is a growing view that to make efficient use of resources, ecological monitoring should be hypothesis-driven and targeted to address specific management questions. 'Targeted' monitoring has been contrasted with other approaches in which a range of quantities are monitored in case they exhibit an alarming trend or provide ad hoc ecological insights. The second form of monitoring, described as surveillance, has been criticized because it does not usually aim to discern between competing hypotheses, and its benefits are harder to identify a priori. The alternative view is that the existence of surveillance data may enable rapid corroboration of emerging hypotheses or help to detect important 'unknown unknowns' that, if undetected, could lead to catastrophic outcomes or missed opportunities. We derive a model to evaluate and compare the efficiency of investments in surveillance and targeted monitoring. We find that a decision to invest in surveillance monitoring may be defensible if: (1) the surveillance design is more likely to discover or corroborate previously unknown phenomena than a targeted design and (2) the expected benefits (or avoided costs) arising from discovery are substantially higher than those arising from a well-planned targeted design. Our examination highlights the importance of being explicit about the objectives, costs and expected benefits of monitoring in a decision analytic framework. ?? 2010 Blackwell Publishing Ltd/CNRS.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1111/j.1461-0248.2010.01514.x","issn":"1461023X","usgsCitation":"Wintle, B., Runge, M., and Bekessy, S., 2010, Allocating monitoring effort in the face of unknown unknowns: Ecology Letters, v. 13, no. 11, p. 1325-1337, https://doi.org/10.1111/j.1461-0248.2010.01514.x.","startPage":"1325","endPage":"1337","numberOfPages":"13","costCenters":[],"links":[{"id":245922,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217949,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1461-0248.2010.01514.x"}],"volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2010-07-30","publicationStatus":"PW","scienceBaseUri":"5059e96ce4b0c8380cd48292","contributors":{"authors":[{"text":"Wintle, B.A.","contributorId":72100,"corporation":false,"usgs":true,"family":"Wintle","given":"B.A.","email":"","affiliations":[],"preferred":false,"id":461968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runge, M.C. 0000-0002-8081-536X","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":49312,"corporation":false,"usgs":true,"family":"Runge","given":"M.C.","affiliations":[],"preferred":false,"id":461966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bekessy, S.A.","contributorId":71424,"corporation":false,"usgs":true,"family":"Bekessy","given":"S.A.","affiliations":[],"preferred":false,"id":461967,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70037615,"text":"70037615 - 2010 - Response of Colorado river runoff to dust radiative forcing in snow","interactions":[],"lastModifiedDate":"2012-03-12T17:22:04","indexId":"70037615","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Response of Colorado river runoff to dust radiative forcing in snow","docAbstract":"The waters of the Colorado River serve 27 million people in seven states and two countries but are overallocated by more than 10% of the river's historical mean. Climate models project runoff losses of 7-20% from the basin in this century due to human-induced climate change. Recent work has shown however that by the late 1800s, decades prior to allocation of the river's runoff in the 1920s, a fivefold increase in dust loading from anthropogenically disturbed soils in the southwest United States was already decreasing snow albedo and shortening the duration of snow cover by several weeks. The degree to which this increase in radiative forcing by dust in snow has affected timing and magnitude of runoff from the Upper Colorado River Basin (UCRB) is unknown. Hereweuse the Variable Infiltration Capacity model with postdisturbance and predisturbance impacts of dust on albedo to estimate the impact on runoff from the UCRB across 1916-2003. We find that peak runoff at Lees Ferry, Arizona has occurred on average 3 wk earlier under heavier dust loading and that increases in evapotranspiration from earlier exposure of vegetation and soils decreases annual runoff by more than 1.0 billion cubic meters or ???5% of the annual average. The potential to reduce dust loading through surface stabilization in the deserts and restore more persistent snow cover, slow runoff, and increase water resources in the UCRB may represent an important mitigation opportunity to reduce system management tensions and regional impacts of climate change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Proceedings of the National Academy of Sciences of the United States of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1073/pnas.0913139107","issn":"00278424","usgsCitation":"Painter, T.H., Deems, J., Belnap, J., Hamlet, A., Landry, C.C., and Udall, B., 2010, Response of Colorado river runoff to dust radiative forcing in snow: Proceedings of the National Academy of Sciences of the United States of America, v. 107, no. 40, p. 17125-17130, https://doi.org/10.1073/pnas.0913139107.","startPage":"17125","endPage":"17130","numberOfPages":"6","costCenters":[],"links":[{"id":499902,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2951423","text":"External Repository"},{"id":218116,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1073/pnas.0913139107"},{"id":246098,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"40","noUsgsAuthors":false,"publicationDate":"2010-09-20","publicationStatus":"PW","scienceBaseUri":"505aaa15e4b0c8380cd8612b","contributors":{"authors":[{"text":"Painter, T. H.","contributorId":98070,"corporation":false,"usgs":false,"family":"Painter","given":"T.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":461931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deems, J.S.","contributorId":40835,"corporation":false,"usgs":true,"family":"Deems","given":"J.S.","email":"","affiliations":[],"preferred":false,"id":461929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, J. 0000-0001-7471-2279","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":23872,"corporation":false,"usgs":true,"family":"Belnap","given":"J.","affiliations":[],"preferred":false,"id":461927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hamlet, A.F.","contributorId":81723,"corporation":false,"usgs":true,"family":"Hamlet","given":"A.F.","affiliations":[],"preferred":false,"id":461930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landry, C. C.","contributorId":108352,"corporation":false,"usgs":false,"family":"Landry","given":"C.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":461932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Udall, B.","contributorId":32766,"corporation":false,"usgs":true,"family":"Udall","given":"B.","email":"","affiliations":[],"preferred":false,"id":461928,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70037224,"text":"70037224 - 2010 - Assessment of basin-scale hydrologic impacts of CO2 sequestration, Illinois basin","interactions":[],"lastModifiedDate":"2012-03-12T17:22:11","indexId":"70037224","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2049,"text":"International Journal of Greenhouse Gas Control","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of basin-scale hydrologic impacts of CO2 sequestration, Illinois basin","docAbstract":"Idealized, basin-scale sharp-interface models of CO2 injection were constructed for the Illinois basin. Porosity and permeability were decreased with depth within the Mount Simon Formation. Eau Claire confining unit porosity and permeability were kept fixed. We used 726 injection wells located near 42 power plants to deliver 80 million metric tons of CO2/year. After 100 years of continuous injection, deviatoric fluid pressures varied between 5.6 and 18 MPa across central and southern part of the Illinois basin. Maximum deviatoric pressure reached about 50% of lithostatic levels to the south. The pressure disturbance (>0.03 MPa) propagated 10-25 km away from the injection wells resulting in significant well-well pressure interference. These findings are consistent with single-phase analytical solutions of injection. The radial footprint of the CO2 plume at each well was only 0.5-2 km after 100 years of injection. Net lateral brine displacement was insignificant due to increasing radial distance from injection well and leakage across the Eau Claire confining unit. On geologic time scales CO2 would migrate northward at a rate of about 6 m/1000 years. Because of paleo-seismic events in this region (M5.5-M7.5), care should be taken to avoid high pore pressures in the southern Illinois basin. ?? 2010 Elsevier Ltd.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Greenhouse Gas Control","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.ijggc.2010.04.004","issn":"17505836","usgsCitation":"Person, M., Banerjee, A., Rupp, J., Medina, C., Lichtner, P., Gable, C., Pawar, R., Celia, M., McIntosh, J., and Bense, V., 2010, Assessment of basin-scale hydrologic impacts of CO2 sequestration, Illinois basin: International Journal of Greenhouse Gas Control, v. 4, no. 5, p. 840-854, https://doi.org/10.1016/j.ijggc.2010.04.004.","startPage":"840","endPage":"854","numberOfPages":"15","costCenters":[],"links":[{"id":245251,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217314,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ijggc.2010.04.004"}],"volume":"4","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ee21e4b0c8380cd49bab","contributors":{"authors":[{"text":"Person, M.","contributorId":20876,"corporation":false,"usgs":true,"family":"Person","given":"M.","email":"","affiliations":[],"preferred":false,"id":459961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banerjee, A.","contributorId":26411,"corporation":false,"usgs":true,"family":"Banerjee","given":"A.","email":"","affiliations":[],"preferred":false,"id":459962,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rupp, J.","contributorId":78128,"corporation":false,"usgs":true,"family":"Rupp","given":"J.","email":"","affiliations":[],"preferred":false,"id":459967,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Medina, C.","contributorId":85440,"corporation":false,"usgs":true,"family":"Medina","given":"C.","email":"","affiliations":[],"preferred":false,"id":459968,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lichtner, P.","contributorId":27719,"corporation":false,"usgs":true,"family":"Lichtner","given":"P.","email":"","affiliations":[],"preferred":false,"id":459963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gable, C.","contributorId":90572,"corporation":false,"usgs":true,"family":"Gable","given":"C.","email":"","affiliations":[],"preferred":false,"id":459969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pawar, R.","contributorId":108346,"corporation":false,"usgs":true,"family":"Pawar","given":"R.","email":"","affiliations":[],"preferred":false,"id":459970,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Celia, M.","contributorId":69394,"corporation":false,"usgs":true,"family":"Celia","given":"M.","affiliations":[],"preferred":false,"id":459965,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McIntosh, J.","contributorId":58872,"corporation":false,"usgs":true,"family":"McIntosh","given":"J.","email":"","affiliations":[],"preferred":false,"id":459964,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bense, V.","contributorId":70624,"corporation":false,"usgs":true,"family":"Bense","given":"V.","affiliations":[],"preferred":false,"id":459966,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70037602,"text":"70037602 - 2010 - Growth, condition factor, and bioenergetics modeling link warmer stream temperatures below a small dam to reduced performance of juvenile steelhead","interactions":[],"lastModifiedDate":"2012-03-12T17:22:06","indexId":"70037602","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2900,"text":"Northwest Science","onlineIssn":"2161-9859","printIssn":"0029-344X","active":true,"publicationSubtype":{"id":10}},"title":"Growth, condition factor, and bioenergetics modeling link warmer stream temperatures below a small dam to reduced performance of juvenile steelhead","docAbstract":"We investigated the growth and feeding performance of juvenile steelhead Oncorhynchus mykiss using field measures and bioenergetics modeling. Juvenile steelhead populations were sampled from mid-June through August 2004 at study sites upstream and downstream of Hemlock Dam. The growth and diet of juvenile steelhead were determined for a warm (summer) and subsequent (late summer) transitional period at each study site. Empirical data on the growth and diet of juvenile steelhead and mean daily temperatures were used in a bioenergetics model to estimate the proportion of maximum consumption achieved by juvenile steelhead by site and period. Modeled estimates of feeding performance were better for juvenile steelhead at the upstream compared to the downstream site during both periods. The median condition factor of juvenile steelhead did not change over the summer at the upstream site, but showed a significant decline over time at the downstream site. A negative trend in median condition factor at the downstream site supported bioenergetics modeling results that suggested the warmer stream temperatures had a negative impact on juvenile steelhead. Bioenergetics modeling predicted a lower feeding performance for juvenile steelhead rearing downstream compared to upstream of Hemlock Dam although food availability appeared to be limited at both study sites during the warm period. Warmer water temperatures, greater diel variation, and change in diel pattern likely led to the reduced feeding performance and reduced growth, which could have affected the overall survival of juvenile steelhead downstream of Hemlock Dam. ?? 2010 by the Northwest Scientific Association.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Northwest Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.3955/046.084.0406","issn":"0029344X","usgsCitation":"Sauter, S., and Connolly, P., 2010, Growth, condition factor, and bioenergetics modeling link warmer stream temperatures below a small dam to reduced performance of juvenile steelhead: Northwest Science, v. 84, no. 4, p. 369-377, https://doi.org/10.3955/046.084.0406.","startPage":"369","endPage":"377","numberOfPages":"9","costCenters":[],"links":[{"id":218034,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3955/046.084.0406"},{"id":246011,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2e10e4b0c8380cd5c28f","contributors":{"authors":[{"text":"Sauter, S.T.","contributorId":13203,"corporation":false,"usgs":true,"family":"Sauter","given":"S.T.","email":"","affiliations":[],"preferred":false,"id":461870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connolly, P.J.","contributorId":70141,"corporation":false,"usgs":true,"family":"Connolly","given":"P.J.","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":461871,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70034072,"text":"70034072 - 2010 - Effects of lipid extraction on stable isotope ratios in avian egg yolk: Is arithmetic correction a reliable alternative?","interactions":[],"lastModifiedDate":"2017-05-07T11:56:19","indexId":"70034072","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Effects of lipid extraction on stable isotope ratios in avian egg yolk: Is arithmetic correction a reliable alternative?","docAbstract":"Many studies of nutrient allocation to egg production in birds use stable isotope ratios of egg yolk to identify the origin of nutrients. Dry egg yolk contains &gt;50% lipids, which are known to be depleted in <sup>13</sup>C. Currently, researchers remove lipids from egg yolk using a chemical lipid-extraction procedure before analyzing the isotopic composition of protein in egg yolk. We examined the effects of chemical lipid extraction on ??<sup>13</sup>C, ??<sup>15</sup>N, and ??<sup>34</sup>S of avian egg yolk and explored the utility of an arithmetic lipid correction model to adjust whole yolk ??<sup>13</sup>C for lipid content. We analyzed the dried yolk of 15 captive Spectacled Eider (Somateriafischeri) and 20 wild King Eider (S. spectabilis) eggs, both as whole yolk and after lipid extraction with a 2:1 chloroform:methanol solution. We found that chemical lipid extraction leads to an increase of (mean ?? SD) 3.3 ?? 1.1% in ??<sup>13</sup>C, 1.1 ?? 0.5% in ??<sup>15</sup>N, and 2.3 ?? 1.1% in ??<sup>34</sup>S. Arithmetic lipid correction provided accurate values for lipid-extracted S13C in captive Spectacled Eiders fed on a homogeneous high-quality diet. However, arithmetic lipid correction was unreliable for wild King Eiders, likely because of their differential incorporation of macronutrients from isotopically distinct environments during migration. For that reason, we caution against applying arithmetic lipid correction to the whole yolk ??<sup>13</sup>C of migratory birds, because these methods assume that all egg macronutrients are derived from the same dietary sources. ?? 2010 The American Ornithologists' Union.","language":"English","publisher":"American Ornithological Society","doi":"10.1525/auk.2009.09153","issn":"00048038","usgsCitation":"Oppel, S., Federer, R., O’Brien, D.M., Powell, A., and Hollmén, T., 2010, Effects of lipid extraction on stable isotope ratios in avian egg yolk: Is arithmetic correction a reliable alternative?: The Auk, v. 127, no. 1, p. 72-78, https://doi.org/10.1525/auk.2009.09153.","productDescription":"7 p.","startPage":"72","endPage":"78","costCenters":[],"links":[{"id":244834,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0746e4b0c8380cd51613","contributors":{"authors":[{"text":"Oppel, S.","contributorId":44001,"corporation":false,"usgs":true,"family":"Oppel","given":"S.","affiliations":[],"preferred":false,"id":443937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Federer, R.N.","contributorId":86599,"corporation":false,"usgs":true,"family":"Federer","given":"R.N.","email":"","affiliations":[],"preferred":false,"id":443939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Brien, D. M.","contributorId":39203,"corporation":false,"usgs":true,"family":"O’Brien","given":"D.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":443936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, A.N.","contributorId":66194,"corporation":false,"usgs":true,"family":"Powell","given":"A.N.","email":"","affiliations":[],"preferred":false,"id":443938,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hollmén, Tuula E.","contributorId":32112,"corporation":false,"usgs":false,"family":"Hollmén","given":"Tuula E.","affiliations":[],"preferred":false,"id":443935,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70037252,"text":"70037252 - 2010 - Standards for documenting and monitoring bird reintroduction projects","interactions":[],"lastModifiedDate":"2019-06-05T08:09:54","indexId":"70037252","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1326,"text":"Conservation Letters","active":true,"publicationSubtype":{"id":10}},"title":"Standards for documenting and monitoring bird reintroduction projects","docAbstract":"<p>It would be much easier to assess the effectiveness of different reintroduction methods, and so improve the success of reintroductions, if there was greater standardization in documentation of the methods and outcomes. We suggest a series of standards for documenting and monitoring the methods and outcomes associated with reintroduction projects for birds. Key suggestions are: documenting the planned release before it occurs, specifying the information required on each release, postrelease monitoring occurring at standard intervals of 1 and 5 years (and 10 for long-lived species), carrying out a population estimate unless impractical, distinguishing restocked and existing individuals when supplementing populations, and documenting the results. We suggest these principles would apply, largely unchanged, to other vertebrate classes. Similar methods could be adopted for invertebrates and plants with appropriate modification. We suggest that organizations publicly state whether they will adopt these approaches when undertaking reintroductions. Similar standardization would be beneficial for a wide range of topics in environmental monitoring, ecological studies, and practical conservation.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1755-263X.2010.00113.x","issn":"1755263X","usgsCitation":"Sutherland, W., Armstrong, D., Butchart, S., Earnhardt, J., Ewen, J., Jamieson, I., Jones, C., Lee, R., Newbery, P., Nichols, J., Parker, K., Sarrazin, F., Seddon, P., Shah, N., and Tatayah, V., 2010, Standards for documenting and monitoring bird reintroduction projects: Conservation Letters, v. 3, no. 4, p. 229-235, https://doi.org/10.1111/j.1755-263X.2010.00113.x.","productDescription":"7 p.","startPage":"229","endPage":"235","numberOfPages":"7","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":475928,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1755-263x.2010.00113.x","text":"Publisher Index Page"},{"id":245220,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-08-02","publicationStatus":"PW","scienceBaseUri":"505b96b3e4b08c986b31b677","contributors":{"authors":[{"text":"Sutherland, W.J.","contributorId":21011,"corporation":false,"usgs":true,"family":"Sutherland","given":"W.J.","email":"","affiliations":[],"preferred":false,"id":460088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Armstrong, D.","contributorId":104486,"corporation":false,"usgs":true,"family":"Armstrong","given":"D.","email":"","affiliations":[],"preferred":false,"id":460098,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butchart, S.H.M.","contributorId":77774,"corporation":false,"usgs":true,"family":"Butchart","given":"S.H.M.","affiliations":[],"preferred":false,"id":460093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Earnhardt, J.M.","contributorId":108344,"corporation":false,"usgs":true,"family":"Earnhardt","given":"J.M.","email":"","affiliations":[],"preferred":false,"id":460099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ewen, J.","contributorId":13466,"corporation":false,"usgs":true,"family":"Ewen","given":"J.","email":"","affiliations":[],"preferred":false,"id":460085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jamieson, I.","contributorId":80120,"corporation":false,"usgs":true,"family":"Jamieson","given":"I.","email":"","affiliations":[],"preferred":false,"id":460094,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, C.G.","contributorId":26164,"corporation":false,"usgs":true,"family":"Jones","given":"C.G.","email":"","affiliations":[],"preferred":false,"id":460089,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lee, R.","contributorId":97153,"corporation":false,"usgs":true,"family":"Lee","given":"R.","affiliations":[],"preferred":false,"id":460097,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Newbery, P.","contributorId":76164,"corporation":false,"usgs":true,"family":"Newbery","given":"P.","email":"","affiliations":[],"preferred":false,"id":460092,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":460086,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Parker, K.A.","contributorId":88182,"corporation":false,"usgs":true,"family":"Parker","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":460095,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sarrazin, F.","contributorId":44390,"corporation":false,"usgs":true,"family":"Sarrazin","given":"F.","email":"","affiliations":[],"preferred":false,"id":460090,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Seddon, P.J.","contributorId":55242,"corporation":false,"usgs":true,"family":"Seddon","given":"P.J.","email":"","affiliations":[],"preferred":false,"id":460091,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Shah, N.","contributorId":91278,"corporation":false,"usgs":true,"family":"Shah","given":"N.","email":"","affiliations":[],"preferred":false,"id":460096,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tatayah, V.","contributorId":15862,"corporation":false,"usgs":true,"family":"Tatayah","given":"V.","affiliations":[],"preferred":false,"id":460087,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70043327,"text":"70043327 - 2010 - Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000","interactions":[],"lastModifiedDate":"2017-04-25T13:10:33","indexId":"70043327","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000","docAbstract":"Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon budgets. Here we use the General Ensemble biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China’s upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to a lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sink/source patterns showed a high degree of spatial heterogeneity. Carbon sinks were associated with forest areas without disturbances, whereas carbon sources were primarily caused by stand-replacing disturbances. It is critical to adequately represent the detailed fast-changing dynamics of land use activities in regional biogeochemical models to determine the spatial and temporal evolution of regional carbon sink/source patterns.","language":"English","publisher":"Springer","doi":"10.1007/s00267-009-9285-9","usgsCitation":"Zhao, S., Liu, S., Yin, R., Li, Z., Deng, Y., Tan, K., Deng, X., Rothstein, D., and Qi, J., 2010, Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000: Environmental Management, v. 45, no. 3, p. 466-475, https://doi.org/10.1007/s00267-009-9285-9.","productDescription":"10 p.","startPage":"466","endPage":"475","ipdsId":"IP-011153","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":271686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Jinsha watershed, Yangtze River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 97.36,21.62 ], [ 97.36,32.38 ], [ 104.08,32.38 ], [ 104.08,21.62 ], [ 97.36,21.62 ] ] ] } } ] }","volume":"45","issue":"3","noUsgsAuthors":false,"publicationDate":"2009-03-19","publicationStatus":"PW","scienceBaseUri":"5180e7ebe4b0df838b924d90","contributors":{"authors":[{"text":"Zhao, Shuqing","contributorId":9152,"corporation":false,"usgs":true,"family":"Zhao","given":"Shuqing","email":"","affiliations":[],"preferred":false,"id":473394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":692785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yin, Runsheng","contributorId":150057,"corporation":false,"usgs":false,"family":"Yin","given":"Runsheng","email":"","affiliations":[{"id":17896,"text":"State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, China","active":true,"usgs":false}],"preferred":false,"id":692786,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Zhengpeng","contributorId":80812,"corporation":false,"usgs":true,"family":"Li","given":"Zhengpeng","affiliations":[],"preferred":false,"id":692787,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deng, Yulin","contributorId":191348,"corporation":false,"usgs":false,"family":"Deng","given":"Yulin","email":"","affiliations":[],"preferred":false,"id":692788,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tan, Kun","contributorId":191349,"corporation":false,"usgs":false,"family":"Tan","given":"Kun","email":"","affiliations":[],"preferred":false,"id":692789,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Deng, Xiangzheng","contributorId":191350,"corporation":false,"usgs":false,"family":"Deng","given":"Xiangzheng","email":"","affiliations":[],"preferred":false,"id":692790,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rothstein, David","contributorId":191351,"corporation":false,"usgs":false,"family":"Rothstein","given":"David","email":"","affiliations":[],"preferred":false,"id":692791,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Qi, Jiaguo","contributorId":191352,"corporation":false,"usgs":false,"family":"Qi","given":"Jiaguo","email":"","affiliations":[],"preferred":false,"id":692792,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70046771,"text":"dds49131 - 2010 - Catchments by major river basins in the conterminous United States: 30-Year average daily minimum temperature, 1971-2000","interactions":[],"lastModifiedDate":"2024-09-25T17:02:12.262653","indexId":"dds49131","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":"491-31","title":"Catchments by major river basins in the conterminous United States: 30-Year average daily minimum temperature, 1971-2000","docAbstract":"This tabular data set represents thecatchment-average for the 30-year (1971-2000) average daily minimum temperature in Celsius 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 Temperature, 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; 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/dds49131","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Catchments by major river basins in the conterminous United States: 30-Year average daily minimum temperature, 1971-2000: U.S. Geological Survey Data Series 491-31, Dataset, https://doi.org/10.3133/dds49131.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":274441,"rank":1,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_tmin30yr.xml"},{"id":274442,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"country":"United States","otherGeospatial":"Conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n      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,{"id":70046768,"text":"dds49128 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Daily Maximum Temperature, 2002","interactions":[],"lastModifiedDate":"2013-11-25T16:06:07","indexId":"dds49128","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":"491-28","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Daily Maximum Temperature, 2002","docAbstract":"This tabular data set represents the average daily maximum temperature in Celsius multiplied by 100 for 2002, compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data were the Near-Real-Time High-Resolution Monthly Average Maximum/Minimum Temperature for the Conterminous United States for 2002 raster data set produced by the Spatial Climate Analysis Service at Oregon State University.\nThe 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; Brakebill and others, 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/dds49128","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Daily Maximum Temperature, 2002: U.S. Geological Survey Data Series 491-28, Dataset, https://doi.org/10.3133/dds49128.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274436,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_tmax02.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":"51d3f662e4b09630fbdc5275","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":480195,"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":480196,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70037535,"text":"70037535 - 2010 - Numerical simulation of a low-lying barrier island's morphological response to Hurricane Katrina","interactions":[],"lastModifiedDate":"2012-03-12T17:22:05","indexId":"70037535","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Numerical simulation of a low-lying barrier island's morphological response to Hurricane Katrina","docAbstract":"Tropical cyclones that enter or form in the Gulf of Mexico generate storm surge and large waves that impact low-lying coastlines along the Gulf Coast. The Chandeleur Islands, located 161. km east of New Orleans, Louisiana, have endured numerous hurricanes that have passed nearby. Hurricane Katrina (landfall near Waveland MS, 29 Aug 2005) caused dramatic changes to the island elevation and shape. In this paper the predictability of hurricane-induced barrier island erosion and accretion is evaluated using a coupled hydrodynamic and morphodynamic model known as XBeach. Pre- and post-storm island topography was surveyed with an airborne lidar system. Numerical simulations utilized realistic surge and wave conditions determined from larger-scale hydrodynamic models. Simulations included model sensitivity tests with varying grid size and temporal resolutions. Model-predicted bathymetry/topography and post-storm survey data both showed similar patterns of island erosion, such as increased dissection by channels. However, the model under predicted the magnitude of erosion. Potential causes for under prediction include (1) errors in the initial conditions (the initial bathymetry/topography was measured three years prior to Katrina), (2) errors in the forcing conditions (a result of our omission of storms prior to Katrina and/or errors in Katrina storm conditions), and/or (3) physical processes that were omitted from the model (e.g., inclusion of sediment variations and bio-physical processes). ?? 2010.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Coastal Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.coastaleng.2010.06.004","issn":"03783839","usgsCitation":"Lindemer, C., Plant, N., Puleo, J., Thompson, D., and Wamsley, T., 2010, Numerical simulation of a low-lying barrier island's morphological response to Hurricane Katrina: Coastal Engineering, v. 57, no. 11-12, p. 985-995, https://doi.org/10.1016/j.coastaleng.2010.06.004.","startPage":"985","endPage":"995","numberOfPages":"11","costCenters":[],"links":[{"id":246008,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218031,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.coastaleng.2010.06.004"}],"volume":"57","issue":"11-12","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6906e4b0c8380cd73b1f","contributors":{"authors":[{"text":"Lindemer, C.A.","contributorId":11862,"corporation":false,"usgs":true,"family":"Lindemer","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":461492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, N.G.","contributorId":94023,"corporation":false,"usgs":true,"family":"Plant","given":"N.G.","email":"","affiliations":[],"preferred":false,"id":461495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Puleo, Jack A.","contributorId":108287,"corporation":false,"usgs":true,"family":"Puleo","given":"Jack A.","affiliations":[],"preferred":false,"id":461496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, D.M.","contributorId":16570,"corporation":false,"usgs":true,"family":"Thompson","given":"D.M.","email":"","affiliations":[],"preferred":false,"id":461493,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wamsley, T.V.","contributorId":60477,"corporation":false,"usgs":true,"family":"Wamsley","given":"T.V.","email":"","affiliations":[],"preferred":false,"id":461494,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70046761,"text":"dds49125 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Surficial Geology","interactions":[],"lastModifiedDate":"2013-11-25T16:05:41","indexId":"dds49125","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":"491-25","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Surficial Geology","docAbstract":"This tabular data set represents the area of surficial geology types in square meters compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data set is the \"Digital data set describing surficial geology in the conterminous US\" (Clawges and Price, 1999).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, 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/dds49125","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Surficial Geology: U.S. Geological Survey Data Series 491-25, Dataset, https://doi.org/10.3133/dds49125.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274415,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_sgeol.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":"51d3f663e4b09630fbdc5281","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":480179,"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":480180,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046735,"text":"dds49113 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Level 3 Nutrient Ecoregions, 2002","interactions":[],"lastModifiedDate":"2013-11-25T16:09:00","indexId":"dds49113","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":"491-13","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Level 3 Nutrient Ecoregions, 2002","docAbstract":"This tabular data set represents the area of each level 3 nutrient ecoregion in square meters compiled for every MRB_E2RF1 catchment of the Major River Basins (MRBs, Crawford and others, 2006). The source data are from the 2002 version of the U.S. Environmental Protection Agency's (USEPA) Aggregations of Level III Ecoregions for National Nutrient Assessment & Management Strategy (USEPA, 2002). 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/dds49113","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Level 3 Nutrient Ecoregions, 2002: U.S. Geological Survey Data Series 491-13, Dataset, https://doi.org/10.3133/dds49113.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274355,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_neco.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":"51d2a4e3e4b0ca18483389ef","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":480135,"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":480136,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046734,"text":"dds49112 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: NLCD 2001 Imperviousness","interactions":[],"lastModifiedDate":"2013-11-25T16:08:32","indexId":"dds49112","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":"491-12","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: NLCD 2001 Imperviousness","docAbstract":"This tabular data set represents the mean percent impervious surface from the Imperviousness Layer of the National Land Cover Dataset 2001,  (LaMotte and Wieczorek, 2010), compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data set represents imperviousness for the conterminous United States for 2001. The Imperviousness Layer of the National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). 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/dds49112","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: NLCD 2001 Imperviousness: U.S. Geological Survey Data Series 491-12, Dataset, https://doi.org/10.3133/dds49112.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":274348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274347,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_imperv.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":"51d2a4e3e4b0ca18483389fb","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":480133,"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":480134,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046731,"text":"dds49109 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Level 3 Ecoregions","interactions":[],"lastModifiedDate":"2013-11-25T16:08:51","indexId":"dds49109","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":"491-09","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Level 3 Ecoregions","docAbstract":"This tabular data set represents the estimated area of level 3 ecological landscape regions (ecoregions), as defined by Omernik (1987), compiled for every MRB_E2RF1 catchment of the Major River Basins (MRBs, Crawford and others, 2006). The source data set is Level III Ecoregions of the Continental United States (U.S. Environmental Protection Agency, 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/dds49109","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Level 3 Ecoregions: U.S. Geological Survey Data Series 491-09, Dataset, https://doi.org/10.3133/dds49109.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274337,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_eco3.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":"51d2a4e2e4b0ca18483389eb","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":480127,"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":480128,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
]}