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Design-based/Model-assisted Survey Methodology for Aquatic Resources

Design-based/Model-assisted Survey Methodology for Aquatic Resources. Don L. Stevens, Jr. Presented at THIRD ANNUAL CONFERENCE: STATISTICAL SURVEY DESIGN AND ANALYSIS FOR AQUATIC RESOURCES Department of Statistics Colorado State University September 10-11, 2004. Designs and Models for.

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Design-based/Model-assisted Survey Methodology for Aquatic Resources

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  1. Design-based/Model-assisted Survey Methodology for Aquatic Resources Don L. Stevens, Jr. Presented at THIRD ANNUAL CONFERENCE: STATISTICAL SURVEY DESIGN AND ANALYSIS FOR AQUATIC RESOURCES Department of Statistics Colorado State University September 10-11, 2004

  2. Designs and Models for Aquatic Resource Surveys DAMARS R82-9096-01 This presentation was developed under STAR Research Assistance Agreement No. CR82-9096-01 Program on Designs and Models for Aquatic Resource Surveys awarded by the U.S. Environmental Protection Agency to Oregon State University. It has not been subjected to the Agency's review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred

  3. Discussion OutlineState of the Program • Personnel • Research • Preview of Presentations • Outreach / Tech Transfer • Summary of Activities • Implications

  4. State of the Program • Personnel • OSU Faculty • Alix Gitelman • Primarily supported by STARMAP • Alan Herlihy • Jointly supported by STARMAP & STAR program on watershed classification • Virginia Lesser • Director of Survey Research Center • PI on Parametric Model Assisted Survey Methods • Don Stevens • Jointly supported by STARMAP • PI on Survey Design Methodology & Integration & Outreach

  5. State of the Program • Personnel • CSU Faculty • Scott Urquhart • Jay Breidt • PI on Non- Parametric Model Assisted Survey Methods • Jointly supported by STARMAP • ISU Faculty • Jean Opsomer • UW Faculty • Loveday Conquest • Jean-Yves (Pip) Courbois • Former post-doc, now with NOAA-Fisheries

  6. State of the Program • Personnel • OSU Post-Doctoral Fellows • Ruben Smith • Breda Munoz-Hernandez • Leaving DAMARS for RTI this fall • OSU Research Associates • Dan Dalthorpe • Joining DAMARS this fall • Jeannie Sifneos • Jointly supported by STAR program on watershed classification • CSU Post-Doctoral Fellow • M. Giovanna Ranalli • Jointly supported by STARMAP

  7. State of the Program • Personnel • OSU Graduate Students • Cynthia Cooper Leigh Ann Harrod (leaving DAMARS for GE) • Kathy Georgitis Susan Hornsby (EPA Region 9 Trainee) • UW Graduate Students • Rebecca Buchanan • USFWS Patuxent Labs intern • Incoming OSU Graduate Students • Bill Gaemon Jessica Merville

  8. Dual Program Objectives • RESEARCH: To support advances in (statistics) and hierarchical survey design and analysis and spatial and temporal modeling • OUTREACH: To develop and extend the expertise on design and analysis to States and Tribes

  9. State of the ProgramResearch • Research is driven by issues that arise in aquatic monitoring • Indicator development/Monitoring Design/Analysis (huge area) • Research topics • Identified in RFA + our experience • Arise from collaboration with EPA, State, other STAR researchers

  10. State of the ProgramResearch • Research presentations will describe on-going research projects • Some will be near-publication status • Some will be snapshots of current progress • Some will be problem descriptions & proposed approaches • Comments, questions, advice are invited in all cases

  11. State of the ProgramResearch • Three projects: • Survey Design Methodology for Aquatic Resources • Parametric Model-Assisted Survey Methods • Nonparametric Model-Assisted Survey Estimation for Aquatic Resources

  12. Don Stevens, PI Pip Courbois Kathi Georgitis Susan Hornsby Loveday Conquest Ruben Smith Cynthia Cooper Rebecca Buchanan Survey Design Methodology for Aquatic Resources

  13. Survey Design Methodology • Survey Design • Variance estimation • Model-assisted approaches • Evaluation of alternative estimators for spatially balanced designs • Maintaining spatially balanced designs • Design around existing points • Modify panel structure of an existing design • Design optimization • Incorporating existing information

  14. Survey Design Methodology • Survey Analysis • Trend estimation using panel designs • Modeling & displaying spatial pattern • Analyzing multi-scale, hierarchical designs • Incorporating non-design data in analysis

  15. Survey Design Methodology • Presentations for this meeting: • Comparison of Variance Estimators for Two-dimensional, Spatially-Structured Sample Designs. Susan Hornsby and Don L. Stevens, Jr. • Comparison of Design-Based and Model-Based Techniques for Selecting Spatially Balanced Samples of Environmental Resources. Don L. Stevens, Jr. • Characterizing Design-Based Properties of a Spatial Sample to Quantify Design-Based Variance of Model-based Estimators. Cynthia Cooper

  16. Survey Design Methodology • Presentations for this meeting: • Sampling Strategies for Chinook-salmon Spawning Populations. Jean-Yves (Pip) Courbois, • Spatio-Temporal Modeling of the Abundance of Spawning Coho in Oregon Coastal Streams. Ruben A. Smith and Don L. Stevens, Jr., • What is a Multi-Scale Analysis? Implications for Modeling Presence/Absence of Bird Species. Kathi Georgitis, Alix Gitelman,, and Nick P. Danz

  17. Survey Design Methodology • Posters for this meeting: • A Cost Analysis for Incorporating Human Judgment into Ecological Sampling. Rebecca A Buchanan and Loveday L. Conquest, University of Washington and Jean-Yves Courbois, NOAA-Fisheries, Northwest Fisheries Sciences Center, Seattle, WA (This poster was displayed and discussed at the Research Symposium of the UW's Center for Water and Watershed Studies, and was judged the runner-up for the Best Poster.) • One-dimensional Point Processes in Ecology. Jean-Yves Courbois, NOAA-Fisheries, Northwest Fisheries Sciences Center, Seattle, WA

  18. Survey Design Methodology • Posters for this meeting: • Defining Scale and Landscape Classes: Implications for Modeling Species Abundance. Kathi Georgitis, Alix Gitelman, Don L. Stevens Jr., Department of Statistics, OSU, Nick P. Danz, and JoAnn M. Hanowski, NRRC- UMD • Two-stage Sampling Designs for Birds in Great Lakes Wetlands. Ron Regal, Dept of Mathematics and Statistics,UMD, Don L. Stevens, Jr., Dept of Statistics, OSU, Nick P. Danz and JoAnn M. Hanowski, NRRC-UMD, and Robert W. Howe, Department of Natural and Applied Sciences, University of Wisconsin-Green Bay

  19. Survey Design Methodology • Manuscripts • 3 published (JASA, JABES, TIES proceedings) • 1 in press Environmetrics • 1 submitted to CJF • 5 in preparation • Presentations • 8 (TIES, Graybill Conference, NABS, workshops) • Posters • 3 (TIES, UW Research Symposium)

  20. Parametric Model Assisted Survey Methods for Environmental Surveys • Virginia Lesser, PI • Breda Munoz • Leigh Ann Harrod

  21. Parametric Model Assisted Survey Methods • Imputation and adjustment • Draws on spatial structure + ancillary data • Treats non-ignorable missing data

  22. Parametric Model Assisted Survey Methods • Presentations this meeting • Use of Estimating Equations in Survey Methodology. Leigh Ann Harrod and Virginia Lesser • Adjustment Procedures to Account for Non-Ignorable Missing Data in Environmental Surveys. Breda Munoz and Virginia Lesser • A Weighting Class Adjustment Estimator for the Total Under a Stratified Sampling Design in a Continuous Domain. Breda Munoz and Virginia Lesser

  23. Parametric Model Assisted Survey Methods • Manuscripts • 1 submitted to Environmetrics • 2 in preparation • Presentations • 1 at TIES

  24. Nonparametric Model Assisted Survey Estimation for Aquatic Resources (CSU Project 2) • F. Jay Breidt, PI • Jean Opsomer • Giovanna Ranalli • Mark Delorey • Alicia Johnson • Siobhan Everson-Stewart • Plus others not supported by either DAMARS or STARMAP

  25. Nonparametric Model Assisted Survey Estimation • Combine landscape-level auxiliary data with field observations. • Local polynomial survey regression estimation • cdf estimation • Non-parametric estimation using penalized splines

  26. Non-Parametric Model Assisted Survey Methods • Presentations this meeting • Nonparametric Survey Regression Estimation Using Penalized Splines. F. Jay Breidt, Jean Opsomer, Giovanna Ranalli and Mark Delorey

  27. Non-Parametric Model Assisted Survey Methods • Posters this meeting • Distribution Function Estimation in Small Areas for Aquatic Resources. Mark J. Delorey, Department of Statistics, CSU • Nonparametric, Model-Assisted Estimation for a Two-Stage Sampling Design. Mark Delorey and F. Jay Breidt, Department of Statistics, CSU

  28. Non-Parametric Model Assisted Survey Methods • Manuscripts • 4 published (JABES, Survey Methodology, proceedings) • 5 submitted (JASA,Biometrics, Can. J. Stat.,Ap. Stat. (JRSSC) • 10 in preparation • Presentations • 8 presentations (EMAP symposium, ENAR, seminars)

  29. Outreach/Tech Transfer • Both DAMARS & STARMAP have same tech transfer objectives, but have different emphases: • STARMAP -- learning materials • DAMARS -- demonstration projects

  30. State of the ProgramOutreach • Success in tech transfer depends on having States, Tribes, (& EPA) use techniques & tools • Foster client use of both design & analysis tools • “build it & they will come” doesn’t work • Need active participation in target projects • Cooperative agreement • Work with EPA • Work on EPA-sponsored projects • Work on projects share EPA goals • Use data generated by EPA projects

  31. State of the Program Outreach • Collaboration that brings statistical perspective to multi-disciplinary research team • Source for new challenges that drives the development of new methodology & theory • Requires high level of commitment • Substantial time requirement • Example: GLEI, an EaGLE STAR Program

  32. Collaboration with GLEIGreat Lakes Environmental Indicators • Kathi Georgitis visited GLEI in November • Identified opportunities for collaboration • where GLEI supplies data & ecological insight • DAMARS statistical insight • Working with Alix Gitelman(OSU), Nick Danz(GLEI), JoAnn Hanowski (GLEI) • Presentation & poster • Ron Regal (GLEI/ UMD) • Optimal allocation for 2-stage sampling in wetlands • See poster by Regal, et al.

  33. State of the Program Outreach • Demonstration Projects • Archetypes used as models • Real-life aquatic monitoring by real State agencies • Push the envelope of State-level monitoring • Design to State-articulated needs • Make them succeed!

  34. Outreach- Demonstration • San Francisco Estuary Regional Monitoring Program for Trace Substances (RMP) • West Coast Tidal Wetland Monitoring and Assessment Venture (CRAM) • Sampling Coho salmon in Oregon coastal streams (ODFW) • Aquatic Monitoring in the Northwest

  35. RMP • Designed monitoring plan for San Francisco Bay • Pulse of the Estuary, 2000 Update • Re-design team: SFEI, USEPA Region 9, DAMARS, USGS, others • Nice example of using prior information to guide design • Implemented in 2001 • Rotating panel GRTS • Intensity varies by Bay segment • Separate designs for water column & sediment

  36. RMP • Re-design report out for peer review

  37. CRAMCalifornia Rapid Assessment Method • Funded by EPA • Joint effort • SFEI –CCC –WED • SCCWRP –DAMARS –Region 9

  38. CRAMCalifornia Rapid Assessment Method • Modeled on Ohio RAM • Extended to cover CA • Salt marshes • Tidal influenced • DAMARS (Stevens) represented on the Core Development Team • Metric/indicator development • Planning for verification/validation study • Pilot assessment

  39. CRAM Metrics • Landscape Context • % of AA w/Buffer • Ave Buffer Width • Buffer Condition • Hydrology • Source of Water • Hydroperiod • Upland connection

  40. CRAM Metrics • Abiotic Structure • Abiotic Patch Richness • Topographic Complexity • Sediment Integrity • Biotic Structure • Organic Matter Accumulation • Biotic Patch Richness • Vertical Structure • Interspersion/Zonation • Plant Comm Integrity

  41. CRAM Metrics • Stressor Index • Hydrology • Abiotic Structure • Biotic Structure • Adjacent Land Use

  42. Stressor Index • Hydrology • Point Sources (POTW or other non-stormwater) • Non-point Source Discharges (urban runoff, ag drainage) • Flow diversions or inflows • Dams (reservoirs, detention basins, recharge basins) • Flow obstructions (culverts, paved stream crossings) • Weir/drop structure, tide gates • Dredged inlet/channel  • Engineered channel (riprap, armored channel bank, bed) • Ditching  • Dike/levees  • Groundwater extraction

  43. ODFW • Focus is on Coho Salmon • High visibility issue in NW (OR, WA, CA, BLM, BPA, USFS, USFWS, NOAA, USEPA) • Rotating panel GRTS is basic sampling design for The Oregon Plan for Salmon & Watersheds • ODFW, OWEB, ODEQ have become our advocates

  44. ODFW • Ideal test bed for design & analysis • Historical data, both probability & convenience • Dynamic frame • Missing data, ignorable & non-ignorable • Ancillary data • Rotating panel through time • Small area estimation • Primary question: Are management efforts having an impact?

  45. ODFW • Oregon Plan for Salmon & Watersheds has been in place for over 5 years • Major synthesis/analysis effort is currently underway • New statistical questions are being raised • How to account for finite support of point sample • Appropriate role of reference data • Appropriate metric for spatial covariance

  46. Pacific salmon on the Washougal River, in Washington.photo by Tom and Pat Leeson

  47. Pacific Rim Salmon Monitoring Strategy for the Conservation of Pacific Salmon State of the Salmon a joint program of Ecotrust and the Wild Salmon Center

  48. Alaska Department of Fish and GameBonneville Power AdministrationFisheries and Oceans CanadaHokkaido Institute of Environmental SciencesHokkaido Fish HatcheryIdaho Fish and GameKhabarovsk Salmon LaboratoryKamchatka Salmon Biodiversity Conservation and Sustainable Use ProgramOregon Department of Fish and Wildlife Oregon State UniversitySalmon Recovery Funding Board USDA Forest ServiceUS Environmental Protection AgencyUS Geological SurveyWashington Department of Fish and WildlifeWild Salmon CenterYakima Klickitat Fisheries Project

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