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Ensemble multispecies modelling and the BlueBRIDGE initiative

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Robert Thorpe, CEFAS, at BlueBRIDGE workshop on "Data Management services to support stock assessement", held during the Annual ICES Science conference 2016

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Ensemble multispecies modelling and the BlueBRIDGE initiative

  1. 1. Ensemble Multispecies modelling and the BLUEBRIDGE initiative Robert Thorpe et al. ICES ASC2016 @ Riga September 2016
  2. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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.

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