1 Software development WP6. 2 Application of FLR Generic Functions from Theory Key parameters...

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1 Software development WP6

Transcript of 1 Software development WP6. 2 Application of FLR Generic Functions from Theory Key parameters...

Page 1: 1 Software development WP6. 2 Application of FLR Generic Functions from Theory Key parameters (theory): q,x,shadow value,enf. cost, prob fine,f Case study.

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Software development

WP6

Page 2: 1 Software development WP6. 2 Application of FLR Generic Functions from Theory Key parameters (theory): q,x,shadow value,enf. cost, prob fine,f Case study.

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Application of FLR• Generic

• Functions from Theory

• Key parameters (theory): q,x,shadow value,enf. cost, prob fine,f

• Case study specific

Page 3: 1 Software development WP6. 2 Application of FLR Generic Functions from Theory Key parameters (theory): q,x,shadow value,enf. cost, prob fine,f Case study.

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Team

• CEFAS: “architecture” and documentation

• IC: modules for calculating new functions (penalty prob.; enforcement cost)

• AZTI: links FLR to databases

• JRC: testing solutions for less experienced users (web access version)

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• Requirement for development of generic code• Implement COBECOS theoretical approach on a

case-study basis• Each case-study has individual requirements• Guidance can be provided• Use simple relationships versus complex (MSE) –

depends on resources, data, linkages to other projects.

COBECOS requirements

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MANAGEMENT PROCEDUREAssess status of stock and set management options depending upon perceived status of fishery stock(s)

Management decision stage

Biological reference

points (e.g. MSY)

FLBRP

Management procedure

FLHCR

MANAGEMENT PROCEDUREAssess status of stock and set management options depending upon perceived status of fishery stock(s)

Management decision stage

Biological reference

points (e.g. MSY)

FLBRP

Management procedure

FLHCR

MANAGEMENT PROCEDUREAssess status of stock and set management options depending upon perceived status of fishery stock(s)

Management decision stage

Biological reference

points (e.g. MSY)

FLBRP

Management procedure

FLHCR

OPERATING MODELRepresents the “true” dynamics

of the system against which performance will be measured

Fleet dynamics

FLFleet

OPERATING MODELRepresents the “true” dynamics

of the system against which performance will be measured

Fleet dynamics

FLFleet

MODEL CONDITIONING

MODEL CONDITIONING

INITIAL CONDITIONS

INITIAL CONDITIONS

IMPLEMENTATION MODEL

FLEcon

IMPLEMENTATION MODEL

FLEcon

IMPLEMENTATION MODEL

FLEcon

IMPLEMENTATION MODEL

FLEcon

Assessment procedure

Assessment assumptions

Auxiliary information(e.g. tuning

indices)

FLIndices

Perceived stock

FLStock

Stock assessment (e.g. VPA)

FLAssess

Assessment procedure

Assessment assumptions

Auxiliary information(e.g. tuning

indices)

FLIndices

Perceived stock

FLStock

Stock assessment (e.g. VPA)

FLAssess

Assessment assumptions

Auxiliary information(e.g. tuning

indices)

FLIndices

Perceived stock

FLStock

Stock assessment (e.g. VPA)

FLAssess

Population biology

Stock dynamics

FLBiol

Stock processese.g. Recruitment

FLSR

Population biology

Stock dynamics

FLBiol

Stock processese.g. Recruitment

FLSR

Stock dynamics

FLBiol

Stock processese.g. Recruitment

FLSR

SUMMARY STATISTICS

Used to evaluate performance of management procedures

against objectives.

SUMMARY STATISTICS

Used to evaluate performance of management procedures

against objectives.

OBSERVATION ERROR MODEL

Generation of data on fishery and

stocks.

FLOEM

OBSERVATION ERROR MODEL

Generation of data on fishery and

stocks.

FLOEM

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• Code for computation of (Fbiol, FLEcon)?– Derive – Monte carlo

• Other functions? (regressions etc)

• Within case study: resources required! (dedication of participants – at case study level)

• Workshop (FLR – one day at IC September)

Work-plan