1 collaborative systemwide monitoring and evaluation project (csmep) presentation to pnamp steering...
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Collaborative Systemwide Monitoring and Evaluation Project (CSMEP)
Presentation to PNAMP Steering Committee
August 21, 2007
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Presentation Outline
1. CSMEP Overview
2. Examples of CSMEP Work Products2.1 Status and Trend M&E2.2 Habitat M&E2.3 Hydro M&E2.4 Hatchery M&E2.5 Harvest M&E2.6 Integration of M&E
3. Summary & Future Plans
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CSMEP is an M&E Coordination Forum for Fish and Wildlife Agencies and Tribes
A forum for Federal, State Agencies and Tribes to collaboratively develop a regional M&E program, consistent with:
– 2000 FCRPS BiOp– Fish and Wildlife Program– Subbasin planning– Recovery Planning
Vision: improve the quality, consistency, and focus
of fish population and habitat data
to answer key M&E questions
relevant to major decisions in the Columbia Basin
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Participants and Approach
CBFWAESSA Technologies Ltd.
State AgenciesIDFGODFWWDFW
Federal AgenciesNOAAUSFWSEPADFO
Tribal AgenciesCRITFCNez Perce TribeColville TribesYakama NationUmatilla Tribes
ConsultantsEco Logical ResearchQuantitative ConsultantsPERWEST
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2.1 Status and Trends M&E
Purpose: Assess viability of the population and overall management scheme.
4H Impacts Actions Monitoring
Harvest √
Hydro √
Habitat √
Hatchery √
Status and Trends will tell you what the population is doing but not why.
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CSMEP Pilot for Snake Basin; learn from this and extend to other regions
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Status and Trends: a Management Example
Priority Question: Are Snake River spring/summer Chinook salmon viable
using IC-TRT guidelines?
Related Decision: Has there been sufficient improvement in the population
status of Snake River spring/summer Chinook salmon to justify delisting and allow removal of ESA restrictions?
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How likely is the correct decision with different levels of monitoring intensity?
Data Needs:• Abundance• Productivity• Spatial structure• Diversity
We used a model to test the ability of monitoring programs to correctly assess spring/summer Chinook salmon population viability in the Snake River ESU using a simulated abundance dataset.
Technical Recovery Team
viability criteria
Viability Status:• Not Viable• Maintained• Viable• Highly Viable
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10
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Status quo
55% correct
A single run of the simulation
Medium
87% correct
High
94% correct
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Objectives by Alternatives Matrix:Status & Trends Designs
Status and Trends Subgroup
.94.87.45.55Pr (making the correct viability assessment for Snake ESU)
Statistical Reliability
2,1007101751,170annual cost of design alternatives (x $1,000)
Cost ($)
GoodFairPoorPoor
ability to make viability assessments for each population in the ESU
Inferential ability (Qualitative)
HighMed Low Status Quo
Design examplesPerformance Measures(Abundance and Spatial
Structure)
Design Objectives
.94.87.45.55Pr (making the correct viability assessment for Snake ESU)
Statistical Reliability
2,1007101751,170annual cost of design alternatives (x $1,000)
Cost ($)
GoodFairPoorPoor
ability to make viability assessments for each population in the ESU
Inferential ability (Qualitative)
HighMed Low Status Quo
Design examplesPerformance Measures(Abundance and Spatial
Structure)
Design Objectives
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Results and Conclusions for Status & Trends M&E
• TRT rule set is conservative, so high uncertainty results in conservative viability assessments.
• Weakness of status quo monitoring design for Snake Pilot:– lack of spatial structure information.– Lack of an abundance estimate in the non-index areas for
populations without weirs. – One MPG lacks a weir.
• The medium design cost less than the status quo, yet performs better (for this question).
• Measurement error may be less than year to year variability, causing small difference between medium and high designs’ reliability
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2.2 Habitat Effectiveness MonitoringLemhi River example
The task:Apply CSMEP’s adapted DQO process to a habitat effectiveness monitoring example
BC
A
A - Lower Mainstem LemhiB - Upper Mainstem LemhiC - Hayden Creek
RST
RST
The Lemhi Habitat Conservation Plan (HCP)
Lemhi Basin: heavily impacted with agriculture diversions and consequent passage issues
• 10-17 tributary reconnection projects planned under Lemhi HCP
• Phased in over the next 35 years
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From Questions to Designs
• To what degree have these actions affected fish populations in the Lemhi Basin?
• Developed a general “Question Clarification Process” to make M&E designs rigorous
• Monitored effects: salmon distribution, survival, productivity
• What are the mechanistic connections between recovery
actions, key habitat attributes and fish responses?
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Information collected with Designs
Design Performance Measures
Status Quo OK for current status and trends data, very limited for habitat effectiveness
Low Fish abundance, juvenile survival, some fish distribution and habitat
Medium Low design + lots of habitat and fish distribution information
High Medium design + juvenile/adult movement, more precise adult returns
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Performance Measures ConsideredData Performance Measure Low Mid High
Redd Counts Adult Abundance
Juvenile Counts @ traps Juvenile Emigrant Abundance
Parr & Smolt Tag detections Parr-Smolt Survival
Snorkel counts (targeted) Juvenile Distribution
Habitat survey (presence) Effect of Actions on Habitat
Snorkel counts (extensive) Parr Density & Distribution
Habitat survey Covariates for fish population response
Adult detection (& tagging) @ Weirs
Adult Returns & Distribution
PIT detections at treatment/control sites
Fish distribution
Juvenile movement
Carcass surveys Prespawn mortality & Adult distribution
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Design Top-Down Bottom-Up
Status Quo
$125,000 $125,000
Low $323,000 $354,000
Mid $377,000 $493,400
High $580,000 $643,600
Top-Down = based on per project costs and contracting history
Bottom-up = based on cost per unit time per person multiplied by the sample sizes identified in the plans.
Costs of CSMEP Designs
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Habitat Effectiveness M&EResults & Conclusions
• Identifying mechanistic effects requires more intense M&E
• Effectiveness monitoring may fulfill requirements of status and trends monitoring
• A one-size-fits-all template for habitat effectiveness monitoring is not workable
• Aspects of the design template for the Lemhi River habitat effectiveness monitoring project may be transferable to other systems.
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2.3 Hydro Action Effectiveness
• Hydro decisions occur at multiple scales:– Operations at individual projects (spill, bypass, RSW)– Overall operations (within season transport, performance
measure compliance)– Longer term hydro decisions (flow, transportation, system
configuration)– Adequacy of hydrosystem operations for population
recovery
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CSMEP Hydro M&E Analyses of Survival Rates(SARs, TIRs, Passage survival)
Spatial Scales ExaminedPopulation (Tributary)
Major Population
Group
Snake River
Aggregate
Time Scales Examined
5-10 year Average
X X X
Annual Estimate
X XSeasonal Estimate
X
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What is our ability to estimate in-river survival from LGR to BON using different M&E designs?
Design 1998 1999 2000 2001 2002 2003 2004 2005 2006
L
SQ, M, H
4 * SQ
Survival exceeds standard Survival below standard
Uncertain, confidence intervals straddle standard
? ? ? ? ? ? ? ?
? ?
? X
?
X X
X
X
X X
X X
X
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Objectives by Alternatives Matrix:Hydro Example – In-River Survival
7/92/91/92/9For wild fish only
GoodPoorPoorPoor…For wild fish alone
7/97/91/97/9For hatchery + wild fish
Fraction of years in which compliance can be clearly assigned (Y/N)Statisticalreliability
11.09.07.88.5Annual cost of design alternatives (x $1,000,000)
Cost ($)
GoodGoodPoorGoodAbility to assess compliance with 2000 FCRPS BiOp in-river survival stds… For hatchery + wild chinook
Inferential ability (Qualitative)
HighMed Low Status Quo
Design AlternativesPerformance MeasuresDesign Objectives
7/92/91/92/9For wild fish only
GoodPoorPoorPoor…For wild fish alone
7/97/91/97/9For hatchery + wild fish
Fraction of years in which compliance can be clearly assigned (Y/N)Statisticalreliability
11.09.07.88.5Annual cost of design alternatives (x $1,000,000)
Cost ($)
GoodGoodPoorGoodAbility to assess compliance with 2000 FCRPS BiOp in-river survival stds… For hatchery + wild chinook
Inferential ability (Qualitative)
HighMed Low Status Quo
Design AlternativesPerformance MeasuresDesign Objectives
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Hydro M&E Conclusions
• Optimal design & confidence level in answers depends on: – spatial and temporal scales– decision criteria, and – true value of parameter being estimated relative to target.
• Increasing number of tags/year: – can improve precision of annual estimates; but– doesn’t help multiple-year averages (# years more important)
• Ability to integrate tags from multiple sources, for multiple questions:– depends on how questions are framed, but– great potential for using PIT-tags, and multi-year averages for
many scales & questions
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Uncertainty regarding the effects of hatchery fish limit management evaluations of :
1. Impacts and benefits of hatcheries.2. De-listing – how do hatchery fish “count” in productivity
estimates?3. Habitat Action Effectiveness – do hatchery fish reduce
Relative Reproductive Success (RRS) and thus mask productivity improvements?
4. Effectiveness of hatcheries for target populations.
2.4 Hatchery Effectiveness
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Hatchery Evaluations
1. Existing hatchery M&E in the basin is primarily focused investigations at the project scale.
2. Assessing more generic hatchery impacts are likely to require larger spatial scale designs.
3. Designs were developed to investigate the effects of hatchery Straying and Relative Reproductive Success.
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What is our ability to assess hatchery straying?
Status Quo• Stray rates/ratios currently calculated using CWT recoveries
in non-random locations.
CSMEP Alternative• Representative distribution of tag recovery effort, increasing
sampling intensity & improved reporting.• No need to sample every population, allows statistical
extrapolation
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Objectives by Alternatives Matrix:Straying
Performance Measures Poor = P, Fair = F, Good = G, Status
QuoLow Med High
Ability to representatively estimate stray ratios and origin of strays in sampled populations.
N/A or P
F G G
Ability to predict stray ratios for unsampled populations.
N/A F G G
Annual/total cost of design alternatives (x $1000)
Statistical Reliability (N)
Maintain coefficient of variation < 0.2
P P G G
Design Objectives Design Alternatives
756/ 6,045
2,503/ 20,025
Inferential ability (Qualitative)
Cost ($)1 432/ 3,456
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Conclusions
• Problems with Status quo– Current straying estimates and RRS studies are not
representative, are likely biased, and cannot be used in a predictive fashion for un-sampled programs or populations.
• CSEMP Designs:– Do not address all hatchery uncertainties.– Focus on PRIMARY uncertainties that limit management
decisions.– Useful for aggregate and individual benefit/risk
evaluations.
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2.5 Harvest Effectiveness M&E
Key Management Decision:
• Open or close fisheries based on allowable Impacts on listed stocks?
Priority Questions:
• What are the in-season, post season estimates of run size & escapement for each management group (target & non-target)?
• How do they compare to preseason estimates?
• What is the target and non-target harvest and when is it projected to reach allowable levels?
.
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Weakness of Current Harvest M&E
• Fisheries are managed to keep listed-stock mortality (“Impacts”) less than permitted rates, but
• Status quo harvest monitoring generally does not provide precision estimates.
• Improved monitoring needed for more accurate and precise information for models (or run reconstructions) used in population viability, status, and trend assessment
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Assess Precision and Bias of Impact Estimates
Consequences of poor (biased or imprecise) estimates
• Underestimate Impact – over harvest of listed stocks
• Overestimate Impact – lost opportunities for user groups
• Poor impact estimates reduce the utility of harvest mortality estimates in run reconstructions, and in assessments of status, trends, and viability
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Identify Areas of Uncertainty and Bias
Columbia River Fisheries• Mainstem Sport• LCR Commercial• Zone 6 Tribal• Tributary
Key Fisheries Metrics• Run-Size Estimates • Stock Composition• Harvest Number• Release Rates • Post-Release Mortality
Rates
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Status Quo
Visual stock ID + Dam Counts + CWT based run reconstruction
Low Status quo + PIT-tag sampling of kept catch under current tagging programs
Medium Representative PIT-tagging of wild populations
CWT-indicator stocks for ESU-level resolution.
Genetic Stock Identification for ESU-level resolution.
High CWT-indicator stocks for MPG-level resolution
GSI for MPG-level stock composition.
Monitoring Design Alternatives
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Harvest M&E Conclusions
1. Run-Size Estimates – improved at modest cost using available data and methods
2. Stock Composition – could be improved with PIT tags, GSI sampling, or index stock
3. Harvest Number – best in commercial fisheries; good in tribal and sport fisheries
4. Release Rates – good in commercial fisheries; potential biases in sport fisheries
5. Post-Release Mortality Rates – are based on limited studies; difficult to estimate
Harvest Subgroup
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2.6 Integration of M&EWhat are the features of an ‘integrated’ monitoring program?
• Scale integration: data can be used at the scale of interest for decisions (e.g. ESUs for viability analysis, population level for local management).
• Integrates across separate monitoring programs: information gathered serves multiple functions (e.g. same PIT-tagged fish used for multiple evaluations); coordinated costing.
• Integrates policy and technical domains: precision of data fits time frames and acceptable risks for decisions.
• Integrates across life history: evaluate survival and habitat requirements throughout the life cycle.
• Species integration: collect data for multiple species in an efficient manner.
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Multiple species
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Status and Trends
Abundance, Productivity, Distribution
Harvest Hatchery
Straying and Relative Reproductive Success studies
Stock compositionAge structure
Hydrosystem
Survival studies
Habitat
Abundance, productivity,spatial structure, spatial diversity changes from habitat actions
PIT Tags
PIT T
ags PIT Tags
PIT
Tag
sP
IT T
ags
Integration example using PIT-tags
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The Future of Collaborative Monitoring
• Collaborative monitoring will become increasingly important as recovery plans are implemented
• Coordination among federal, state and tribal agencies remains critical for developing logical cost-effective M&E (especially for fish populations that cross state and tribal boundaries)
• CSMEP provides a forum for federal, state and tribal fish managers to develop cost-effective, and coordinated regional monitoring for status and trends and the 4-“H”s.
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Questions?
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