Ensemble Multispecies modelling and the BLUEBRIDGE initiative

Robert Thorpe et al.ICES ASC2016 @ Riga

September 2016

Contents

• What is the LeMans Model?

• What can it do?

• Why do we need BlueBridge to help?

• What benefits will there be to the consortium?

LeMans Model Framework

• Species and size-structured• Intermediate complexity model• Conservation of energy in predator/prey link• Life-history traits determine species’ response• Fish community focus, not whole ecosystem

SMS LeMANS Ecopath/Ecospace

Data-drivenTactical

Energy-flow drivenStrategic

LeMans Model Framework (2)

• 21 stocks, 32 size classes

• 10 assessed stocks, inc. cod, haddock, herring, sprat, saithe, sole, whiting

• 11 non-assessed stocks

• 78,125 model variants considered

LeMans Model Framework (3)• Energy requirements, growth, diet composition,

mortality, stock recruitment all represented as functions of length.

• Growth trajectories determined by von Bertalanffy parameters, L infinity and k.

• Diet matrix used along with size to determine what eats what.

• Uncertainties in life history, predation size-selectivity, non-predation natural mortality, stock recruitment, energy needed for growth, diet matrix addressed by ensemble approach

Contents

• What is the LeMans Model?

• What can it do?

• Why do we need BlueBridge to help?

• What benefits will there be to the consortium?

LFI versus Risk by Fleet

Good relationship for otter fleet

Poor for beam and industrial

Intermediate for pelagics

LFI primarily an index of cod and saithe, so better performance for otter fleet is expected

Risk/Reward through PGY Ranges

• Circles are central estimates.

• Spread due to fleet uncertainty.

• Risk is estimated from parameter spreads

• Green region = multispecies precautionary

In the highest part of the ranges, risk increases whilst yield goes down.

Risk increases by 8x, yield by 20% from bottom to top of ranges

Visualising Multispecies MSY

Yield/Risk plots allow multispecies trade-offs to be explicitly presented.

Corresponding fishing solutions can be recovered from modelling.

Information can be used to guide management advice.

2 million simulations

Model uncertaintyFleet management uncertainty.

4 idealised fleets – beam, otter, industrial, pelagicMMSY == fleet combination giving

maximum precautionary yield

Impact of Gear Changes

HISTORIC STECFEACH FLEET CATCHES ONLY 1 STOCK

4 fleets, beam, otter, pelagic, industrial ~2 million simulations eachParameter and fishing scenario uncertainty

Contents

• What is the LeMans Model?

• What can it do?

• Why do we need BlueBridge to help?

• What benefits will there be to the consortium?

Methodology

651 fleet scenarios:Otter BeamIndustrialPelagic

Determine plausible optionsLiterature review

78,125 member UE

Filter against historic data

188 member FE

Identify key parametersHall et al., 2006

2.57M forecasts:parameter, scenario, and management uncertainty

Consider impacts on risk and economic yield. What % are multispecies precautionary?

21 FMSY targets

Contents

• What is the LeMans Model?

• What can it do?

• Why do we need BlueBridge to help?

• What benefits will there be to the consortium?

Benefits

• Demonstration of supercomputing capability as applied to management

• Development of ICES multi-species community model.

• Increased collaboration between ICES partners.

• Better risk based advice.