October 5, 2018

Tasks

Develop MSY reference points or proxies across the spectrum of data-limited stocks.

Simulation Framework, as a number of data-limited methods already exist implement a common framework to compare their performance

Diagnostics to assess sensitivity to assumptions and bias.

Management Strategy Evaluation to ensure robustness to uncertainty

Simulation Framework

Life Histories

Case Studies

Turbot, Brill, Pollack, Ray, Sprat, Lobster, Razors

Natural Mortality

Biology

Equilibrium and Reference Points

Operating Model

Sensitvity Analysis

Elasticity

Reference Points

Elasticity

Reference Points

Elasticity

Population Growth Rate

Elasticity

Mean age at virgin and \(F_{MSY}\), and \(L_{opt}\)

Elasticity

Species

Length v Catch Methods

Scenarios

Stock trends

Evaluation

Length Based Methods

Observation Error Model

Selection pattern

Evaluation

Turbot Example

Operating Model

Category 1: Age based

Category 1: Biomass based

Category 3: Catch only

LBSPR

Fishing Mortality

MLZ

MSE

Performance Measures

Safety

  • Probability of avoiding limits

Status

  • Probability of achieving targets, recovery and long-term

Yield

  • MSY

Variability

  • Annual variability in yield

Cat 1; Aged based ICES AR

Cat 1; Biomass based ICES AR

Cat 1; Comparison

Empirical HCRs

Index Relative to Reference

Empirical HCRs

Trend in Index

Compare Performance

Conclusions

Conclusions

Risk

An uncertainty that matters, what matters are management objectives

Management Procedures

Consider the data along with the assumptions, estimator and management and feedback between the various elements

Value of infomation

Models are cheap, but data is expensive

Diagnostics

Compare across species, stocks, fisheries and advice rules

R Packages

  • FLR
    • FLife
    • mydas
    • mpb
  • R Packages
    • LBSPR
    • MLZ