1. Ensemble Multispecies modelling
and the BLUEBRIDGE initiative
Robert Thorpe et al.
ICES ASC2016 @ Riga
September 2016

2. 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?

3. 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-driven
Tactical
Energy-flow driven
Strategic

4. 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

5. 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

6. 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?

7. 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

8. 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

9. 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 uncertainty
Fleet management
uncertainty.
4 idealised fleets – beam, otter,
industrial, pelagicMMSY == fleet combination giving
maximum precautionary yield

10. Impact of Gear Changes
HISTORIC STECF
EACH FLEET CATCHES
ONLY 1 STOCK
4 fleets, beam, otter, pelagic, industrial ~2 million simulations each
Parameter and fishing scenario uncertainty

11. 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?

12. Methodology
651 fleet
scenarios:
Otter
Beam
Industrial
Pelagic
Determine
plausible
options
Literature
review
78,125
member
UE
Filter
against
historic
data
188
member
FE
Identify key
parameters
Hall 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

13. 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?

14. 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.