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

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
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

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Survey Design Methodology for Aquatic Resources

• Don Stevens, PI
• Pip Courbois
• Kathi Georgitis
• Susan Hornsby

• Loveday Conquest
• Ruben Smith
• Cynthia Cooper
• Rebecca Buchanan

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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

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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

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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

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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

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Parametric Model Assisted Survey Methods

• Imputation and adjustment
• Draws on spatial structure ancillary data
• Treats non-ignorable missing data

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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

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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

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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

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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

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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)

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Outreach/Tech Transfer

• Both DAMARS STARMAP have same tech transfer
  objectives, but have different emphases
• STARMAP -- learning materials
• DAMARS -- demonstration projects

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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 doesnt 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

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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

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CRAMCalifornia Rapid Assessment Method

• Funded by EPA
• Joint effort
• SFEI CCC WED
• SCCWRP DAMARS Region 9

39
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

40
CRAM Metrics

• Landscape Context
• of AA w/Buffer
• Ave Buffer Width
• Buffer Condition
• Hydrology
• Source of Water
• Hydroperiod
• Upland connection

41
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

42
CRAM Metrics

• Stressor Index
• Hydrology
• Abiotic Structure
• Biotic Structure
• Adjacent Land Use

43
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

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45
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

46
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?

47
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

48
Pacific salmon on the Washougal River, in
Washington.photo by Tom and Pat Leeson
49
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
50
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
51
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
52
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
53
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
54
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
55
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
56
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
57
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
58
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
59
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
60
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
61
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
62
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
63
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
64
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
65
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
66
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 University Salmon
Recovery Funding Board USDA Forest ServiceUS
Environmental Protection AgencyUS Geological
SurveyWashington Department of Fish and
WildlifeWild Salmon CenterYakima Klickitat
Fisheries Project
67
Pacific Rim Salmon key elements

• A sampling design that imposes three hierarchical
  levels of organization uniquely defined by
  biology, space, and time (Level 1, Level 2, Level
  3).
• An approach that implements sampling within each
  Level using fixed and rotating panels tailored to
  provide statistically valid assessments of status
  and trends.

68
Pacific Rim Salmon key elements

• An approach that, to the greatest extent
  possible, provides for a seamless integration of
  existing monitoring programs with new monitoring
  initiatives.
• A focus on four key parameters (distribution,
  diversity, abundance, and productivity) that can
  provide an integrated measure of salmon
  population viability.

69
Pacific Rim Salmon key elements

• An effort to forge synergistic relationships with
  in-country fisheries management and conservation
  entities, as well as international organizations
  focusing on conservation of salmon and their
  ecosystems.

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73
Columbia Systemwide Monitoring and Evaluation
Program(CSMEP)

• Collaboratively inventory existing monitoring
  data relevant to evaluating the status of salmon,
  steelhead, bull trout in the Columbia Basin
• Collaboratively design improved monitoring and
  evaluation methods
• Coordinate state and tribal implementation of
  pilot or large scale monitoring programs

74
CSMEP

• Lead agency Columbia Basin Fish and Wildlife
  Authority
• Co-sponsors NOAA-F USFWS, WDFW, ODFW, IDFG,
  MFWP, Fish Passage Center, Columbia River
  Inter-Tribal Fish Commission (Nez Perce, Yakima,
  Umatilla, Warm Springs Tribes) and the Colville
  Tribes
• Also involved Northwest Power and Conservation
  Council Pacific Northwest Aquatic Monitoring
  Partnership