towards standardization of mse algorithms - is there a minimum mse ?

Towards standardization of MSE algorithms

Is there a minimum MSE ?

Ernesto Jardim*Colin Millar

Iago MosqueiraFinlay ScottChato Osio

JRC Unit of Maritime Affairs

Fishreg* ernesto.jardim@jrc.ec.europa.eu

Why ?

➔ Growing demand to set up long term management plans (LTMP) for commercial stocks.

➔ Growing number of data moderate stocks that require LTMP type of analysis.

➔ Management Strategy Evaluation (MSE) is a powerful tool to test how uncertainty, decision making and implementation of management actions impact LTMP objectives.

a4a Init

However ...

a4a Init

MSEs are extremely complex and require:

➔ Long time to develop

➔ Human resources with strong statistical and coding background

Furthermore, MSE results are difficult to communicate

a4a

a4a Init

The Joint Research Center “assessment for all” initiative (a4a) started in 2012, with the aim of:

➔ Develop, test and distribute the necessary methods to assess a large numbers of stocks in an operational time frame.

➔ Build the necessary capacity on stock assessment and advice provision.

a4a

a4a Init

➔ Core team: group of fisheries scientists from the EC JRC responsible for development.

➔ Members: small but global network of scientists from different fisheries research and advice institutions.

➔ Supporting group: network of scientists

➔ Stock assessment: [N], [F]➔ Short term forecast: [Ny+] | [F], [R]➔ Medium term forecast: [Ny++] | [F], [S/R], error(s)

➔ MSE: [Ny++] | [F], [S/R], error(s) +

decision making, implementation error, obs. error

a4a Init

From stock assessment to MSE

a4a Init

MSE

a4a Init

Standardization

1. Identify the most important processes within the MSE framework e.g. OM (partially done).

2. Implement methods in R/FLR to deal with uncertainty in each process in a transparent way (partially done).

3. Identify a limited number of models for each process based on groups of species or sea basins (to be done).

a4a Init

Components of a standard MSE

➔ Operating modelnatural mortality, growth, S/R, exploitation pattern

➔ Management procedureindicator to inform HCR, HCR shape

➔ Observation error modelerror in catch, error in the abundance index

➔ Implementation error modelerror in effective F, overcatch

a4a Init

Example standard management procedure

➔ Three HCR➔ Model-free (no assessment)➔ Relative (based on relative stock status)➔ Absolute (ICES MSY rule)

➔ Four indicators➔ Commercial catch➔ Survey biomass➔ Biomass dynamic SSB/Bmsy & F/Fmsy➔ SC@A SSB & F

a4a Init

(loosely based on S.aurita in Northwest Africa)

a4a Init

Disadvantages

Wrapping up

a4a Init

➔ Important advantages in making MSE widely used:➔ Engage stakeholders in designing management

plans/actions.➔ Makes available sophisticated algorithms.➔ Improves awareness of uncertainty and impacts

on management goals.

➔ Standard MSE for moderate data stocks has to include the most important processes.