Privitera-Johnson General Exam

Kristin Privitera-Johnson


Producing scientific advice in a changing world

A working title


Scientific Motivation

How do you know when you’re successful? From a single-species point-of-view you may want to know things like:

  • Reference points:
    • What is B and/or F?
    • How does B and/or F compare to historical B and/or F?
  • Population dynamics:
    • How do B and F influence average net production rates?
    • How do components of net production vary over time?

Broad research questions pt. 1

Broad research questions pt. 2

“All models are wrong but some are useful”

  • How can analysts leverage this principle to evaluate management strategies?
  • How can modelling efforts influence management outcomes?
  • How have some of these modelling efforts lead to surprising management outcomes?
    • What did analysts learn from these surprises (and apply that to future modelling)?

Chapter Themes

  • Ch. 1: Phase-in HCR et al.
  • Ch. 2: Assessment frequency vs. increasing scientific uncertainty buffers
  • Ch. 3: Incorporating multimodel inference into a climate-linked MSE framework
  • Ch. 4: MSE Interviews

Chapters 1-2 Status Updates

  • Ch. 1: Phase-in HCR et al.
    • Analysis ongoing.
    • Target dates end of academic year
  • Ch. 2: Assessment frequency vs. increasing scientific uncertainty buffers
    • Toy model stage.
    • Target date 2023-2024 Academic Year

Chapters 3-4 Status Updates

  • Ch. 3: Incorporating multimodel inference into a climate-linked MSE framework
    • Theoretical stage.
    • Target date 2023-2024 Academic Year or 2024 calendar year
  • Ch. 4: MSE Interviews
    • Exploring semi-structured interviews.
    • Target date End of 2023 calendar year

Chapter 1

Ch. 1 Questions

  • What happens to management quantities of interest when catch stability mechanisms are used to minimize interannual variation in catch when new stock assessments result in a major increase or decrease in the overfishing limit?
  • How well do phase-in and catch limit restraints perform when a new assessment model leads to changes in the estimates of natural mortality, stock-recruit steepness, catch history, and selectivity form for long- and short-lived stocks?

Methods Breakdown

Simulation Design

Catch Stability Mechanisms

Updating the phase-in HCR

MSE performance metrics

Chapter 2

Ch. 2 Questions

  • What are the potential costs associated with lost yield relative to the cost of conducting another assessment within a ten-year assessment interval?

  • How does assessment bias (by way of assessment frequency and increasing scientific uncertainty buffers) influence management quantities of interest for various levels of attained catch for target and nontarget stocks?

    • Catch limits are taken completely (100% attainment)
    • Catch limits are less than the Annual Catch Limits
    • Catch limits are set for a stock that interacts with another stock

Comparisons to be made

  • a baseline time series generated with annual assessments and no increasing scientific uncertainty buffers

with increasing scientific uncertainty buffers:

  • time series generated with new assessments every 2 years
  • time series with new assessments every 5 years
  • time series with a new assessment in the tenth year

Chapter 3

Ch. 3 Questions

  • Can an ensemble modeling approach mitigate the consequences of model misspecification associated with selecting a single climate model for forecasts and assessments?
  • Does it matter where along the MSE process the ensemble modeling takes place? i.e., How do the reference points change when
  • a single estimation method using model output from an ensemble of climate models
  • an ensemble of estimation method output consisting of one estimation method for each climate model

Methods Breakdown

Simulation Design

Bayesian model-based weights: Spence et al.

Bayesian model-based weights pt. 2

Potential HCRs

Chapter 4

Ch. 4 Questions

  • Which factors influence the range of uncertainties addressed in an MSE?
  • What are examples of implemented meta-rules for tactical MSEs?
  • Which jurisdictions have conducted multiple MSEs for a fishery?
  • Which uncertainties were addressed in each MSE and why?
  • Are there common factors that influence the use of insufficient ranges of uncertainty when performance was inadequate or subsequent monitoring results were surprising?

Methods Breakdown

  • To summarize which uncertainties were prioritized in the surveyed MSEs and how the range of uncertainties addressed changed over time and over multiple applications of MSEs and/or meta-rules for a single fishery, when applicable.

Interview themes

Continued discussion