WKGMSE3
a) Develop guidelines for when and how reference points should be extracted from an MSE when one is conducted.
b) Develop guidelines for how to treat the results of alternative operating models. Currently, these have been used as robustness tests for “optimised” management strategies.
tRFMO Glossary & OM Review
- Conditioning is The process of fitting an Operating Model (OM) of the resource dynamics to the available data on the basis of some statistical criterion, such as a Maximum Likelihood. The aim of conditioning is to select those OMs consistent with the data and reject OMs that do not fit these data satisfactorily and, as such, are considered implausible.
- Plausibility is the likelihood of a scenario considered in simulation trials representing reality, relative to other scenarios also under consideration. Plausibility may be estimated formally based on some statistical approach, or specified based on expert judgement, and can be used to weight performance statistics when integrating over results for different scenarios (OMs).
- Examples
Subsequent work
- Invariance v Consistency Invariance means “even add new data in retro analysis, no change in the past”. Retro analysis is analysis but invariance is a property. Might be better just to say consistency.
- Cognitive Science A definition of a highly plausible scenario is one that fits prior knowledge well: with many different sources of corroboration, without complexity of explanation, and with minimal conjecture .
- Plausibility may be estimated formally based on a statistical approach, or specified based on expert judgement, and can be used to weight performance across summary statistics related to yield and sustainability when integrating over results for different OM scenarios representing alternative hypotheses.
- Robustness An alternative is rather than weighting a large number of scenarios, to be acceptable a strategy must perform well across all scenarios that pass a selection criteria. In either case the choice of the OMs and weighting schemes are critical.
Examples
- Cookbook Best assessment and rejecting
- WKENSENBLE Weight
- ICES Benchmarking Advice
- Hindcast Prediction skill
- Albacore and Yellowfin
d) Develop more efficient ways of conducting searches over a grid to the required level of precision be investigated. This is needed because of the high-performance computing requirements for full MSEs. This work could include investigating statistical properties that relate sample size to required precision, GAMs to interpolate over an incomplete grid, etc.
e) Compare the short-cut and full MSE approaches, providing guidelines for use of the former as an approximation for the latter, if appropriate. Consideration should be given to MSE with alternative operating models (i.e. operating models not solely based on the currently-used assessment).