Grantee Research Project Results
2003 Progress Report: Applying Spatial and Temporal Modeling of Statistical Surveys to Aquatic Resources
EPA Grant Number: R829095Center: Space-Time Aquatic Resources Modeling and Analysis Program (STARMAP)
Center Director: Urquhart, N. Scott
Title: Applying Spatial and Temporal Modeling of Statistical Surveys to Aquatic Resources
Investigators: Urquhart, N. Scott , Hoeting, Jennifer A. , Davis, Richard A. , Breidt, F. Jay , Iyer, Hariharan K. , Theobald, David M.
Current Investigators: Urquhart, N. Scott , Hoeting, Jennifer A. , Davis, Richard A. , Gitelman, Alix I. , Ritter, Kerry J. , Breidt, F. Jay , Iyer, Hariharan K. , Stevens, Don L. , Theobald, David M. , Johnson, Devin S. , Opsomer, Jean
Institution: Colorado State University , Southern California Coastal Water Research Project Authority , Oregon State University
Current Institution: Colorado State University , Iowa State University , Oregon State University , Southern California Coastal Water Research Project Authority , University of Alaska - Fairbanks
EPA Project Officer: Packard, Benjamin H
Project Period: October 1, 2001 through September 30, 2006
Project Period Covered by this Report: October 1, 2002 through September 30, 2003
Project Amount: $2,998,331
RFA: Research Program on Statistical Survey Design and Analysis for Aquatic Resources (2001) RFA Text | Recipients Lists
Research Category: Water , Aquatic Ecosystems , Ecological Indicators/Assessment/Restoration , Watersheds
Objective:
The objectives of this research project are: (1) the development and implementation of statistical methods for aquatic surveys; (2) communication of results to States and Tribes; and (3) training of future generations of environmental statisticians.
This is a general progress report for STARMAP (R829095). The progress reports for the specific research projects conducted by the Center are reported separately (see reports for R829095C001 through R829095C005).
Progress Summary:
In broad outline, the Space-Time Aquatic Resources Modeling and Analysis Program (STARMAP) is proceeding consistently with its proposal, except for its rate of completion of the second year’s work. The Director judges that approximately three-fourths of the work proposed for the first two years has been completed. About 60 percent of the first 2 years’ funds have been expended. Lack of success in recruiting postdoctoral fellows is the main reason for both the delayed rate of completion of work and the low expenditure of funds. Recruiting efforts for postdoctoral fellows is being vigorously pursued, but alternatives for accomplishing the research are being implemented, as recommended by the Program’s Science Advisory Committee. Specifically, we are developing part-time relations with several junior statisticians and anticipate an involvement for them something like postdoctoral fellows.
The program Designs and Models for Aquatic Resource Surveys (DAMARS), in cooperation with STARMAP, sponsored the Second Annual Conference on Statistical Survey Design and Analysis for Aquatic Resources at Oregon State University, August 11 - 13, 2003. This conference involved major contributions from both programs, the Programs’ Science Advisory Committee, persons from EPA, individuals from other federal agencies, as well as other interested participants, mainly from OSU. Students from both programs had major roles in this conference presenting talks and posters.
During this reporting period STARMAP personnel have published one scientific paper, have five in press, have two manuscripts under journal review; they have completed one doctoral and three masters theses, one technical report, and have at least 16 manuscripts in various stages of preparation. These personnel made more than 40 professional presentations (about 2/3 invited), and displayed 5 posters. They have participated in at least 24 professional venues, ranging from departmental seminars to international conferences, and made presentations in at least 21 of them. All STARMAP students have attended at least one professional meeting and made at least one presentation or presented a poster; collectively they attended 10 professional meetings making presentations at 8 of them. Details appear in the individual subproject reports.
Substantial progress has been made in the direction of local area estimation for eventual use in projecting from a sample of data points to other unobserved location. New methods for analyzing discrete composition data of the sort resulting from collections of aquatic macroinvertebrate have been developed; their utility will be further explored in collaboration with data resulting from the efforts of other investigators funded by STAR. GIS techniques for accomplishing spatially distributed probability of aquatic resources have been implemented and now nearly are ready to begin being tested.
Two recent STARMAP efforts relate to time-space modeling. A doctoral seminar course, led by Breidt and Davis, explored current literature on spatial-temporal analysis. This course was presented by 10 doctoral statistics students, assisted by two faculty and two senior staff members. EPA prepared a report to Congress on effects of the Clean Air Act Amendments, specifically its effect on trends in the acidification of surface waters. The underlying data involves both probability and purposefully-picked sites, data across time (10+ years), and space - of the scale of the northeastern US, and trend as the primary response. Most of the topics in this advanced seminar concern solutions, but this contemporary EPA situation was considered in all of its real complexity. All of the data from this study is now available for STARMAP participants. We anticipate features of this complex situation will be considered by several students.
We are working on five different subprojects: Combing Environmental Data Sets; Local Inference; Indicator Development; Integration and Outreach; and Integration and Administration. Individual subproject results can be found in the Annual Summary Reports of those projects.
Future Activities:
We will continue to develop and implement statistical methods for aquatic surveys. We will communicate our results to states and tribes and help to train future generations of environmental statisticians.
Journal Articles: 43 Displayed | Download in RIS Format
Other center views: | All 291 publications | 55 publications in selected types | All 43 journal articles |
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Andrews B, Davis RA, Breidt FJ. Maximum likelihood estimation for all-pass time series models. Journal of Multivariate Analysis 2006;97(7):1638-1659. |
R829095 (Final) R829095C002 (2003) R829095C002 (2004) R829096 (2003) |
Exit Exit |
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Andrews B, Davis RA, Breidt FJ. Rank-based estimation for all-pass time series models. Annals of Statistics 2007;35(2):844-869. |
R829095 (2005) R829095 (Final) R829095C002 (2003) R829095C002 (2004) |
Exit Exit Exit |
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Breidt FJ, Hsu N-J. Best mean square prediction for moving averages. Statistica Sinica 2005;15(2):427-446. |
R829095 (Final) R829095C002 (2003) R829095C002 (2004) R829095C002 (2005) R829096 (2003) R829096 (2005) |
Exit Exit |
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Breidt FJ, Claeskens G, Opsomer JD. Model-assisted estimation for complex surveys using penalised splines. Biometrika 2005;92(4):831-846. |
R829095 (Final) R829095C002 (2003) R829095C002 (2005) |
Exit Exit |
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Breidt FJ, Opsomer JD, Johnson AA, Ranalli MG. Semiparametric model-assisted estimation for natural resource surveys. Survey Methodology 2007;33(1):35-44. |
R829095 (Final) R829095C002 (2003) R829095C002 (2004) |
Exit Exit |
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Breidt FJ, Hsu N-J, Ogle S. Semiparametric mixed models for increment-averaged data with application to carbon sequestration in agricultural soils. Journal of the American Statistical Association 2007;102(479):803-812. |
R829095 (2005) |
Exit |
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Brockwell PJ, Davis RA, Yang Y. Continuous-time Gaussian autoregression. Statistica Sinica 2007;17(1):63-80. |
R829095 (Final) |
Exit Exit |
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Courbois JP, Urquhart NS. Comparison of survey estimates of the finite population variance. Journal of Agricultural, Biological, and Environmental Statistics 2004;9(2):236-251. |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C003 (2003) R829095C003 (2004) R829096 (2003) R829096 (2004) R829096 (2005) |
Exit |
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Da Silva DN, Opsomer JD. Properties of the weighting cell estimator under a nonparametric response mechanism. Survey Methodology 2004;30(1):45-55. |
R829095 (2003) R829095 (2004) R829095 (2005) R829095 (Final) R829095C002 (2004) R829095C002 (2005) R829096 (2004) R829096 (2005) |
Exit Exit |
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Dailey M, Gitelman AI, Ramsey FL, Starcevich S. Habitat selection models to account for seasonal persistence in radio telemetry data. Environmental and Ecological Statistics 2007;14(1):55-68. |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C001 (2005) |
Exit |
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Davis RA, Dunsmuir WTM, Streett SB. Observation-driven models for Poisson counts. Biometrika 2003;90(4):777-790. |
R829095 (Final) |
Exit Exit |
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Davis RA, Rodriguez-Yam G. Estimation for state-space models based on a likelihood approximation. Statistica Sinica 2005;15(2):381-406. |
R829095 (Final) R829095C001 (2005) |
Exit Exit |
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Davis RA, Lee TCM, Rodriguez-Yam GA. Structural break estimation for nonstationary time series models. Journal of the American Statistical Association 2006;101(473):223-239. |
R829095 (Final) |
Exit Exit |
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Farnsworth ML, Hoeting JA, Hobbs NT, Miller MW. Linking chronic wasting disease to mule deer movement scales:a hierarchical Bayesian approach. Ecological Applications 2006;16(3):1026-1036. |
R829095 (Final) |
Exit Exit |
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Francisco-Fernandez M, Opsomer JD. Smoothing parameter selection methods for nonparametric regression with spatially correlated errors. Canadian Journal of Statistics 2005;33(2):279-295. |
R829095 (Final) R829095C002 (2004) R829095C002 (2005) |
Exit Exit |
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Francisco-Fernandez M, Jurado-Exposito M, Opsomer JD, Lopez-Granados F. A nonparametric analysis of the spatial distribution of Convolvulus arvensis in wheat-sunflower rotations. Environmetrics 2006;17(8):849-860. |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C002 (2004) R829095C002 (2005) |
Exit Exit |
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French J. Confidence regions for the level curves of spatial data. ENVIRONMETRICS 2014;25(7):498-512 |
R829095 (Final) |
Exit |
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Gitelman AI, Herlihy A. Isomorphic chain graphs for modeling spatial dependence in ecological data. Environmental and Ecological Statistics 2007;14(1):27-40. |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C001 (2005) |
Exit |
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Hall P, Opsomer JD. Theory for penalised spline regression. Biometrika 2005;92(1):105-118. |
R829095 (Final) R829095C002 (2005) |
Exit |
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Hoeting JA, Davis RA, Merton AA, Thompson SE. Model selection for geostatistical models. Ecological Applications 2006;16(1):87-98. |
R829095 (Final) R829095C001 (2004) R829095C001 (2005) R829095C004 (2005) |
Exit Exit |
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Hoeting JA. Some perspectives on modeling species distributions. Bayesian Analysis 2006;1(1):93-98. (Comment on article by Gelfand et al.). |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C001 (2005) |
Exit Exit |
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Johnson AA, Breidt FJ, Opsomer JD. Estimating distribution functions from survey data using nonparametric regression. Journal of Statistical Theory and Practice 2008;2(3):419-431. |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C002 (2003) R829095C002 (2005) |
Exit |
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Johnson DS, Hoeting JA. Autoregressive models for capture-recapture data:a Bayesian approach. Biometrics 2003;59(2):341-350. |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C001 (2003) |
Exit Exit |
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Johnson DS, Hoeting JA. Bayesian multimodel inference for geostatistical regression models. PLoS ONE 2011;6(11):e25677. |
R829095C001 (2005) |
Exit |
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Kahl JS, Stoddard JL, Haeuber R, Paulsen SG, Birnbaum R, Deviney FA, Webb JR, DeWalle DR, Sharpe W, Driscoll CT, Herlihy AT, Kellogg JH, Murdoch PS, Roy K, Webster KE, Urquhart NS. Peer Reviewed: Have U.S. surface waters responded to the 1990 Clean Air Act Amendments? Environmental Science & Technology 2004;38(24):484A-490A. |
R829095 (2004) R829095 (2005) R829095 (Final) |
Exit Exit Exit |
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Kauermann G, Opsomer JD. Generalized cross-validation for bandwidth selection of backfitting estimates in generalized additive models. Journal of Computational & Graphical Statistics 2004;13(1):66-89. |
R829095 (Final) R829095C002 (2005) |
Exit Exit |
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Kincaid TM, Larsen DP, Urquhart NS. The structure of variation and its influence on the estimation of status: indicators of condition of lakes in Northeast, U.S.A. Environmental Monitoring and Assessment 2004;98(1-3):1-21. |
R829095 (Final) R829095C003 (2003) R829095C003 (2004) |
Exit |
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Larsen DP, Kincaid TM, Jacobs SE, Urquhart NS. Designs for evaluating local and regional scale trends. Bioscience 2001;51(12):1069-1078. |
R829095 (2004) R829095 (2005) R829095 (Final) |
Exit |
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Larsen DP, Kaufmann PR, Kincaid TM, Urquhart NS. Detecting persistent change in the habitat of salmon-bearing streams in the Pacific Northwest. Canadian Journal of Fisheries and Aquatic Sciences 2004;61(2):283-291. |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C003 (2003) R829095C003 (2004) |
Exit Exit |
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Montanari GE, Ranalli MG. Nonparametric model calibration estimation in survey sampling. Journal of the American Statistical Association 2005;100(472):1429-1442. |
R829095 (Final) R829095C002 (2004) R829095C002 (2005) R829096 (2004) R829096 (2005) |
Exit |
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Opsomer JD, Botts C, Kim JY. Small area estimation in a watershed erosion assessment survey. Journal of Agricultural, Biological, and Environmental Statistics 2003;8(2):139-152. |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C002 (2004) R829096 (2004) R829096 (2005) |
Exit Exit |
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Opsomer JD, Miller CP. Selecting the amount of smoothing in nonparametric regression estimation for complex surveys. Journal of Nonparametric Statistics 2005;17(5):593-611. |
R829095 (Final) R829095C002 (2004) R829095C002 (2005) |
Exit |
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Opsomer JD, Breidt FJ, Moisen GG, Kauermann G. Model-assisted estimation of forest resources with generalized additive models. Journal of the American Statistical Association 2007;102(478):400-409. |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C002 (2004) R829095C002 (2005) R829096 (2003) R829096 (2004) R829096 (2005) |
Exit Exit |
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Opsomer JD, Claeskens G, Ranalli MG, Kauermann G, Breidt FJ. Non-parametric small area estimation using penalized spline regression. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2008;70(1):265-286. |
R829095C002 (2005) R829096 (2005) |
Exit Exit |
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Opsomer JD, Francisco-Fernandez M. Finding local departures from a parametric model using nonparametric regression. Statistical Papers 2010;51(1):69-84. |
R829095C002 (2005) |
Exit |
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Peterson EE, Merton AA, Theobald DM, Urquhart NS. Patterns of spatial autocorrelation in stream water chemistry. Environmental Monitoring and Assessment 2006;121(1-3):571-596. |
R829095 (Final) |
Exit Exit |
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Peterson EE, Urquhart NS. Predicting water quality impaired stream segments using landscape-scale data and a regional geostatistical model: a case study in Maryland. Environmental Monitoring and Assessment 2006;121(1-3):615-638. |
R829095 (2005) R829095 (Final) |
Exit Exit |
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Reese GC, Wilson KR, Hoeting JA, Flather CH. Factors affecting species distribution predictions: a simulation modeling experiment. Ecological Applications 2005;15(2):554-564. |
R829095 (Final) R829095C001 (2005) |
Exit Exit |
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Ritter KJ, Leecaster MK. Multi-lag cluster designs for estimating the semivariogram for sediments affected by effluent discharges offshore in San Diego. Environmental and Ecological Statistics 2007;14(1):41-53. |
R829095 (Final) |
Exit Exit |
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Thomas DL, Johnson D, Griffith B. A Bayesian random effects discrete-choice model for resource selection: population-level selection inference. Journal of Wildlife Management 2006;70(2):404-412. |
R829095 (Final) R829096 (2005) |
Exit |
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Ver Hoef JM, Peterson E, Theobald D. Spatial statistical models that use flow and stream distance. Environmental and Ecological Statistics 2006;13(4):449-464. |
R829095 (Final) |
Exit Exit |
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Waite IR, Herlihy AT, Larsen DP, Urquhart NS, Klemm DJ. The effects of macroinvertebrate taxonomic resolution in large landscape bioassessments: an example from the Mid-Atlantic Highlands, U.S.A. Freshwater Biology 2004;49(4):474-489. |
R829095 (Final) R829095C003 (2004) R829498 (2003) R829498 (Final) |
Exit |
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Wang H, Ranalli MG. Low-rank smoothing splines on complicated domains. Biometrics 2007;63(1):209-217. |
R829095 (2004) R829095 (2005) R829095 (Final) R829095C002 (2005) |
Exit Exit |
Supplemental Keywords:
latent processes, Matern covariance function, model selection, remote sensing, sampling design, path Analysis, kernel regression, thin plate splines, small area estimation, GIS, tessellation stratified sampling, water quality, land cover, land use, accuracy, precision, outreach, distance learning, web-based learning, needs-based instruction, accommodating cultural differences, management, efficiency,, RFA, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, Aquatic Ecosystems & Estuarine Research, climate change, Air Pollution Effects, Aquatic Ecosystem, Environmental Monitoring, Atmosphere, EMAP, ecosystem monitoring, statistical survey design, spatial and temporal modeling, aquatic ecosystems, water quality, Environmental Monitoring and Assessment ProgramRelevant Websites:
http://www.stat.colostate.edu/starmap Exit
Progress and Final Reports:
Original Abstract Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R829095C001 Combining Environmental Data Sets
R829095C002 Local Inferences from Aquatic Studies
R829095C003 Development and Evaluation of Aquatic Indicators
R829095C004 Extension of Expertise on Design and Analysis to States and Tribes
R829095C005 Integration and Coordination for STARMAP
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.