Ecosystemscale optimization policies: Gulf of Thailand

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Ecosystem-scale optimization policies Gulf of
Thailand
Villy Christensen Carl Walters
UBC Fisheries Centre
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Time predictions from an ecosystem model of the
Georgia Strait, 1950-2000
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Are we finally able to develop useful predictive
models for ecosystem management?

• Its beginning to look like it
• Recent success in replicating population history
  for a series of ecosystems
• We can with some credibility describe agents of
  mortality and trophic interdependencies
• Now we need to test how models predict policy
  choices.

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Optimum fishing policy
Ecosim (www.ecopath.org) provides formal
optimization methods to search for fishing
policies that would maximize a particular policy
goal or objective function for management.
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Policy objectives

• Maximize fisheries rent
• Maximize social benefits
• Maximize mandated rebuilding
• Maximize ecosystem structure
• We evaluate the fleet configurations that
  optimize each of these conflictive objectives
  (individually or jointly)

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Gulf of Thailand
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Gulf of Thailand
1960s trawling started 1980s severely
overfished
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Landings
1963
1973
Value

• Increasing importance of invertebrates
• Large fish (gt30 cm) disappear

Weight
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Optimizing profits

• Profits are calculated as landed value of the
  catch less the cost of fishing
• Often optimization is achieved by
• reducing effort
• phasing out most fleets except the most
  profitable ones and
• hitting ecosystems groups competing with or
  preying on the more valuable target species.

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Optimizing profits
Value
1973
103
Weight
1973
79
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Effort, profit optimization

• Profits 154
• Value 103
• Effort 96
• Catch 79

2 14 29 3 30
1 Baseline profit () 32 8
0 48 0
17 Shrimp in catch () 1 12
40 2 1 45 Total
profit ()
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Optimizing profits

• Value of catch increases slightly
• Profits increase 50
• Total effort hardly change, but fleets are
  favored very differently (unselective trawl and
  fine-meshed push net nearly stopped)
• Catch composition change toward valuable species
• Does not imply simplification of the ecosystem.

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Optimizing social benefits

• 1 Social benefits are expressed through the
  employment supported by each fleet
• The benefits are calculated as fleet specific
  jobs/value of catch

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1973 profits jobs
Value
Weight
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Effort, job optimization

• Effort 212
• Value 177
• Catch 107
• Profits -84

3 41 22 1 6
27 Catch (baseline, ) 4 27
21 2 5 41 Value
(baseline, )
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Optimization for food security

• Effort gtgt
• Catch 191
• Profits ltlt

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Mandated rebuilding

• External pressure (or legal decisions) may force
  policy makers to concentrate on preserving or
  rebuilding the population of a given species in a
  given area
• In Ecosim set a threshold biomass, and optimize
  towards the fleet effort structure that will
  ensure this objective
• Exemplified in Gulf of Thailand example by
  setting an arbitrary target of doubling the
  marine mammal (dolphin) biomass.

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Mandated rebuilding

• Effort 250
• Value 93
• Catch 36
• Profits ltlt

• Severe economic consequences if performed
  mindlessly

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Maximizing ecosystem structure

• The ecosystem structure definition is inspired
  by Odums description of ecosystem maturity
  wherein mature ecosystems are dominated by large,
  long-lived organisms
• The group-specific biomass/production ratio
  provides the default weighting factor for the
  maximization of overall biomass

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Optimizing ecosystem structure
L. piscivores
Rays
Catfish
Sharks
Snapper
Marine mammals
Scomberomorus
Coastal tuna
Grunts
Scad
Juv. scad
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Ecosystem structure optimization

• Catch 30
• Effort 24
• Value 24
• Profits 18

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Catch vs.trophic level
?
Optimizing profits
?
?
Optimizing jobs
Optimizing ecology
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Biomass diversity
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Effort for profits, jobs ecology optim.
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Cooperation vs. competition
Effort
F (catch/biomass)
One for all
Fleet by fleet
Total catch
Total value
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Balancing objectives Paulys favorite

• 1 lost leg
• 1 war
• 2 wives
• 1 ulcer
• 5

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Balancing objectives

• The starting values of the objective functions
  have each been standardized relative to their
  base values (from Ecopath)
• Equal weighting, in essence, means that an
  increase in profit of, e.g., 10 is considered to
  have the same value to society as a 10 increase
  in jobs or ecosystem structure.

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Optimizing profits jobs
Profits
Jobs (value)
Ecology
Weight on jobs
Diversity
TL of catch
Catch weight
Weight on profits
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Optimizing profits ecology
Profits
Jobs (value)
Ecology
Weight on ecology
Diversity
TL of catch
Catch weight
Weight on profits
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Optimizing ecology and jobs
Profits
Jobs (value)
Ecology
Weight on jobs
Diversity
TL of catch
Catch weight
Weight on ecology
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Conclusion

• Optimizations (even for only one objective) leads
  to less radical configurations than expected
• There can be weightings that improve the
  situation for all objectives
• Thus, the beast is much better behaved than we
  could have hoped for

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End