cdfg sjr fall run chinook salmon model cwemf november 4 2005
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CDFG SJR Fall-run Chinook Salmon Model CWEMF November 4, 2005. Objectives. Brief Overview of Model Development Describe Model Structure Describe Model Calibration/Validation Describe Model Scenarios. Overview. San Joaquin River Salmon Production as a function of Spring Vernalis Flow.

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Presentation Transcript
objectives
Objectives
  • Brief Overview of Model Development
  • Describe Model Structure
  • Describe Model Calibration/Validation
  • Describe Model Scenarios
overview
Overview

San Joaquin River Salmon Production as a function of Spring Vernalis Flow

study area
Study Area

Courtesy of USFWS

salmon cohort singe year production indicator
Salmon Cohort“Singe Year Production Indicator”

Brood Year Production Juvenile

Age 1

Age 5

Age 2

Age 4

Age 3

CWT Recovery

Scale Analysis

salmon escapement multi year production indicator
Salmon Escapement“Multi-Year Production Indicator”

Age 1

Year 1

Annual Carcass “Creamer” Survey

Age 2

Year 2

Age 3

Year 3

Age 4

Year 4

Age 5

Year 5

1995 wqcp triennial review
1995 WQCP Triennial Review
  • CDFG Challenge:
    • Are the Flow Objectives Working?
        • What is the status of the salmon population?
        • What fraction of juvenile salmon are receiving protection?
        • What is the status of the VAMP experiment?
populations are declining

1983-1995 Average 42,285

1996-2004 Average 35,004

SJ Basin Production

Year

Populations Are Declining
vamp implementation
VAMP Implementation
  • VAMP:
      • Lock Down Uncertainty at Extremes First
      • Since 2000:
  • Result:
      • Continued uncertainty
      • Need several successive high flow range tests to define/solidify relationship
2005 swrcb 95 wqcp review
2005 SWRCB ’95 WQCP Review
  • CDFG:
      • presented its concerns
      • asked for peer review
  • SWRCB:
      • peer reviewed already occurred
      • CDFG: develop flow recommendations
chalkboard
Chalkboard

E = mc?

What +/- What = More Salmon?

Harvest?

Exports?

Disease?

Predation?

Flow?

Gravel?

model logic
Model Logic
  • Delta Exports
      • weak correlation to cohort production
model logic1
Model Logic
  • Ocean Harvest
        • weak correlation to cohort production

Harvest - Sacramento, San Joaquin and CVI

Ocean Harvest versus Tuolumne Escapement

model logic2

Mossdale Smolts

Previous Year Escapement

Model Logic
  • Adult Stock Density Limitations

Ricker Stock-recruit relationship (density dependent mortality governor) appears questionable

More females = more juveniles (Tuolumne River)

adult stock density limitations
Adult Stock Density Limitations

Density Dependent Governor ?

Higher Escapement

Higher Spring Flow

Higher Cohort Production

Higher Escapement

Lower Spring Flow

Lower Cohort Production

Multiple Regression

1973-1999

R-square = 0.75

P = .001

Tuolumne River data

model logic3
Model Logic
  • Instream Flow

Strong correlation to cohort production in relation to spring flow

SJB east-side tributaries principle flow & salmon contributor

flow features
Flow Features
  • Increased Vernalis Flow Magnitude/Duration/Frequency all projected increased adult salmon production
now what
Now What?
  • Challenge: “How to link salmon life history production to flow magnitude & duration?”
  • Solution: “Develop a tool”
model concept
Model Concept
  • Flow primary driving factor in population (not harvest, exports or adult stock density)
  • Quantify relationships between:
    • flow and juvenile production
    • flow and juvenile survival
    • juvenile survival and adult escapement
  • Simulate production over time
model features
Model Features
  • Excel spreadsheet platform
  • Links life history stages by numerical production at each phase
  • Predicts adult escapement (1967-2000)
  • Flow duration & magnitude variable
  • Predicts escapement change & water volume
  • Has 95% confidence level predictions
  • Customizable input parameters
model refinements
Model Refinements
  • Limits predictions to data set
  • Uses San Joaquin Basin data for age cohort reconstruction
  • Smolt Outmigration pattern WY Type specific
  • Allows for HORB/non-HORB smolt survival
  • 95% confidence levels predictions
conceptual model
Conceptual Model

Vernalis Flow

Mossdale Smolts

Delta Survival

Adult Cohort

Annual Escapement (spawners)

Chipps Smolts

Escapement Reconstruction

conceptual model1
Conceptual Model

Vernalis Flow

Mossdale Smolts

Delta Survival

Adult Cohort

Annual Escapement (spawners)

Chipps Smolts

Escapement Reconstruction

conceptual model2
Conceptual Model

Vernalis Flow

Mossdale Smolts

Delta Survival

Adult Cohort

Annual Escapement (spawners)

Chipps Smolts

Escapement Reconstruction

repeat cycle
Repeat Cycle

Combine spawners with Vernalis flow to predict Mossdale Smolt Production

Vernalis Flow

Mossdale Smolts

Delta Survival

Adult Cohort

Annual Escapement (spawners)

Chipps Smolts

Escapement Reconstruction

model calibration validation
Model Calibration & Validation
  • Two Approaches
      • Calibrate with subset/validate with remaining
      • Calibrate with entire data set
  • Parameters
      • Escapement pattern
      • Time period average
      • Replacement ratio
      • Stay within 95% CI
sj basin escapement 1967 2000
SJ Basin Escapement 1967-2000

-----Historic -----Modeled

95 confidence intervals
95% Confidence Intervals

HistoricUpper 95% CILower 95% CI

model scenarios
Model Scenarios
  • Ten model runs
  • Four presented
what scenarios
What Scenarios
  • Possible Goal Attainment Scenarios
      • Vary Flow with Window Constant
        • VAMP (3200-7000 with 31 day window)
      • Constant Flow & Window Constant
        • 10,000 all WY Types & 31 day window
      • Constant Flow & Variable Window
        • 10,000 all WY Types & Variable WY Window
      • Variable Flow & Variable Window
        • 5-20K Flow & 31-90 day Window
conclusion
Conclusion

Stanislaus River

San Joaquin River

what now
What Now?
  • Model Documentation
  • Release Model/Report
  • Model Refinements
  • Peer Review
      • Develop questions
peer review questions
Peer Review Questions
  • What is the best way to test model results?
  • Is there a better population health barometer than “replacement ratio and escapement”?
  • What is the influence of cascading confidence intervals?
  • Other Questions?
input questions
Input & Questions
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