Applying Spatial and Temporal Modeling of Statistical Surveys to Aquatic Resources

EPA Grant Number: R829095
Center: 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 , Breidt, F. Jay , Davis, Richard A. , Gitelman, Alix I. , Herlihy, Alan T. , Hoeting, Jennifer A. , Iyer, Hariharan K. , Johnson, Stephen , Loftis, James C. , Reich, Robin M. , Ritter, Kerry J. , Stevens, Don L. , Theobald, David M. , Weisberg, Steven B.
Current Investigators: Urquhart, N. Scott , Breidt, F. Jay , Davis, Richard A. , Gitelman, Alix I. , Hoeting, Jennifer A. , Iyer, Hariharan K. , Johnson, Devin S. , Opsomer, Jean , Ritter, Kerry J. , Stevens, Don L. , Theobald, David M.
Institution: Colorado State University , Oregon State University , Southern California Coastal Water Research Project Authority
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 Amount: $2,998,331
RFA: Research Program on Statistical Survey Design and Analysis for Aquatic Resources (2001) RFA Text |  Recipients Lists
Research Category: Water , Ecosystems , Aquatic Ecosystems , Ecological Indicators/Assessment/Restoration , Water and Watersheds

Objective:

This Program will extend existing EMAP survey design and analysis methodology to enhance the use of auxiliary information, to apply recent advances in statistical modeling techniques to aquatic resources, and to develop model-based methodology compatible with EMAP's multi-tiered studies; to implement these techniques on example data sets; to provide expert survey design and analysis assistance to States and Tribes; and to transfer that statistical expertise to States, Tribes and local agencies through a combination of supervised application of statistical tools and structured distance learning techniques.

Approach:

The Program proposed here will initiate statistical research on several well-defined topics in model-based inference: Combining environmental data, local prediction of environmental responses, and the development and evaluation of indicators of environmental responses. We have identified some statistical research needs coupled with existing EMAP data sets and appropriate for similar data sets to be gathered by the States and Tribes. We will develop model-based analysis methods to meet those needs. We have established liaisons with some state, tribal and local organizations who are using (or plan to use) EMAP or EMAP-like surveys of aquatic resources. We will strengthen and expand those contacts to include all identifiable State and Tribal agencies who are using (or plan to use) EMAP, REMAP, or EMAP-like surveys of aquatic resources. We will assist those agencies in applying existing survey design and analysis methods, and, in particular, investigate and extend techniques for incorporating auxiliary information in the design. In collaboration with those agencies and other State and Tribal organizations, we will identify further statistical research needs to be addressed by our statistical methodology research teams and extend model-based analyses as necessary. Further, we will explore various distance learning techniques with our collaborators, and use their feedback to refine our techniques.

Expected Results:

The Program proposed here will substantially improved methodology for assessing the condition of aquatic resources at all levels: national, multiple state regions, state, tribal, and local. The proposed program will also improve the awareness of that methodology by the parties who should use it, and will expand the cadre of statisticians with the experience and expertise to collaborate with aquatic scientists and resource managers on monitoring aquatic resources.

The Program is designed to accomplish five major goals:

  • Extend model-based statistical methodology to cover the unique circumstances encountered in EMAP-like situations.
  • Extend both existing and newly-developed model-based statistical tools to be more accessible to State, Tribal, and local agency personnel, both the aquatic scientists and managers of aquatic resources.
  • Expand the pool of personnel in the States, Tribes, and local agencies who have both understanding of and experience in using these statistical tools.
  • Develop and train a cadre of statisticians with the experience and expertise to collaborate on monitoring aquatic resources.
  • Develop three archetypes of rigorous probability-based, state or local monitoring programs, along with archetype model-based analyses, incorporating landscape scale features into the analysis. The existence of these archetypes will benefit efforts to build state, tribal, and local infrastructure to monitor the condition of the
  • Nation's aquatic resources.

Relevant Websites: http://www.stat.colostate.edu/starmap Exit


Journal Articles: 42 Displayed | Download in RIS Format

Other center views: All 302 publications 54 publications in selected types All 42 journal articles
Type Citation Sub Project Document Sources
Journal Article 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)
  • Full-text: ScienceDirect-Full Text PDF
    Exit
  • Abstract: ScienceDirect-Abstract
    Exit
  • Journal Article 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)
  • Full-text: Project Euclid-Full Text PDF
    Exit
  • Abstract: Project Euclid-Abstract
    Exit
  • Other: Cornell University-Full Text PDF
    Exit
  • Journal Article 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)
  • Full-text: StatisticaSinica-Full Text PDF
    Exit
  • Abstract: StatisticaSinica-Abstract
    Exit
  • Journal Article 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)
  • Abstract: Oxford Journals-Abstract
    Exit
  • Other: Ku Leuven-Prepublication PDF
    Exit
  • Journal Article 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)
  • Full-text: Statistics Canada-Full Text PDF
    Exit
  • Abstract: Statistics Canada-TOC
    Exit
  • Journal Article 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)
  • Abstract: Journal of the American Statistical Association-Abstract
    Exit
  • Journal Article Brockwell PJ, Davis RA, Yang Y. Continuous-time Gaussian autoregression. Statistica Sinica 2007;17(1):63-80. R829095 (Final)
  • Full-text: Statistica Sinica - Full Text PDF
    Exit
  • Abstract: Statistica Sinica - Abstract
    Exit
  • Journal Article 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)
  • Abstract: SpringerLink
    Exit
  • Journal Article 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)
  • Full-text: Statistics Canada-Full Text PDF
    Exit
  • Abstract: Statistics Canada-Abstract
    Exit
  • Journal Article 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)
  • Abstract: Springer - Abstract
    Exit
  • Journal Article Davis RA, Dunsmuir WTM, Streett SB. Observation-driven models for Poisson counts. Biometrika 2003;90(4):777-790. R829095 (Final)
  • Abstract: Biometrika - Abstract
    Exit
  • Other: Columbia University-Full Text PDF
    Exit
  • Journal Article 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)
  • Full-text: Institute of Statistical Science Academia Sinica-Full Text PDF
    Exit
  • Abstract: Statistica Sinica-Abstract
    Exit
  • Journal Article 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)
  • Full-text: University of California-Full Text PDF
    Exit
  • Abstract: Taylor & Francis-Abstract
    Exit
  • Journal Article 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)
  • Abstract from PubMed
  • Full-text: Colorado State University-Full Text PDF
    Exit
  • Abstract: Ecological Applications-Abstract
    Exit
  • Journal Article 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)
  • Full-text: Universidade da Coruna-Preprint PDF
    Exit
  • Abstract: Wiley-Abstract
    Exit
  • Journal Article 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)
  • Full-text: Universidade da Coruna-Prepublication PDF
    Exit
  • Abstract: Wiley Interscience Abstract
    Exit
  • Journal Article 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)
  • Abstract: SpringerLink Abstract
    Exit
  • Journal Article Hall P, Opsomer JD. Theory for penalised spline regression. Biometrika 2005;92(1):105-118. R829095 (Final)
    R829095C002 (2005)
  • Abstract: Biometrika
    Exit
  • Journal Article 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)
  • Abstract from PubMed
  • Full-text: Colorado State University-Full Text PDF
    Exit
  • Abstract: ESA-Abstract
    Exit
  • Journal Article 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)
  • Full-text: Carnegie Mellon University-Full Text PDF
    Exit
  • Abstract: Carnegie Mellon University-Abstract
    Exit
  • Journal Article 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)
  • Abstract: Taylor&Francis-Abstract
    Exit
  • Other: Journal Issue Contents
    Exit
  • Journal Article 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)
  • Abstract from PubMed
  • Full-text: Colorado State University-Full Text PDF
    Exit
  • Abstract: Wiley-Abstract
    Exit
  • Journal Article Johnson DS, Hoeting JA. Bayesian multimodel inference for geostatistical regression models. PLoS ONE 2011;6(11):e25677. R829095C001 (2005)
  • Full-text: PLoS ONE-Full Text HTML & PDF Link
    Exit
  • Journal Article 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)
  • Abstract from PubMed
  • Full-text: University of Virginia-Full Text PDF
    Exit
  • Abstract: ES&T-Abstract
    Exit
  • Other: Research Gate-Full Text PDF
    Exit
  • Journal Article 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)
  • Full-text: Research Gate-Abstract and Full Text HTML
    Exit
  • Abstract: Taylor & Francis - Abstract
    Exit
  • Journal Article 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)
  • Abstract from PubMed
  • Abstract: Springer-Abstract
    Exit
  • Journal Article 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)
  • Abstract: BioOne Abstract
    Exit
  • Journal Article 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)
  • Full-text: Instituto de Ciencias Biologicas-Full Text PDF
    Exit
  • Abstract: NRC Research Press Abstract
    Exit
  • Journal Article 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)
  • Abstract: American Statistical Association-Abstract
    Exit
  • Journal Article 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)
  • Full-text: Research Gate-Abstract and Full Text HMTL
    Exit
  • Abstract: SpringerLink-Abstract
    Exit
  • Journal Article 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)
  • Abstract: Taylor & Francis-Abstract
    Exit
  • Journal Article 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)
  • Full-text: US Forest Service-Full Text PDF
    Exit
  • Abstract: Journal of the American Statistical Association-Abstract
    Exit
  • Journal Article 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)
  • Abstract: Wiley
    Exit
  • Other: Prepublication PDF
    Exit
  • Journal Article Opsomer JD, Francisco-Fernandez M. Finding local departures from a parametric model using nonparametric regression. Statistical Papers 2010;51(1):69-84. R829095C002 (2005)
  • Abstract: SpringerLink-Abstract
    Exit
  • Journal Article 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)
  • Abstract from PubMed
  • Full-text: Research Gate-Full Text PDF
    Exit
  • Abstract: SpringerLink-Abstract
    Exit
  • Journal Article 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)
  • Abstract from PubMed
  • Full-text: Research Gate-Abstract and Full Text HTML
    Exit
  • Abstract: SpringerLink-Abstract
    Exit
  • Journal Article 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)
  • Full-text: U.S. Forest Service-Full Text PDF
    Exit
  • Abstract: Ecological Society of America-Abstract
    Exit
  • Journal Article 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)
  • Abstract: Springer - Abstract
    Exit
  • Other: Southern California Coastal Water Research Project-Report PDF
    Exit
  • Journal Article 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)
  • Abstract: Wiley-Abstract
    Exit
  • Journal Article 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)
  • Full-text: University of Nebrask-Lincoln-Full Text PDF
    Exit
  • Abstract: SpringerLink
    Exit
  • Journal Article 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)
  • Abstract: Wiley - Abstract
    Exit
  • Journal Article 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)
  • Abstract from PubMed
  • Abstract: Wiley Interscience-Abstract
    Exit
  • Other: BNU-PrepublicationFull Text PDF
    Exit
  • Supplemental Keywords:

    public policy, decision making, community-based, monitoring, risk assessment, watersheds, surface waters, estuaries, Bayesian, hierarchical modeling, GIS, landscape, 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 Program

    Progress and Final Reports:

  • 2002
  • 2003 Progress Report
  • 2004 Progress Report
  • 2005 Progress Report
  • Final Report
  • 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