ecosystem-scale optimization policies incofish ewe workshop, cape town, september 2006 incofish ewe...
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![Page 1: Ecosystem-scale optimization policies IncoFish EwE Workshop, Cape Town, September 2006 IncoFish EwE Workshop, Cape Town, September 2006 Villy Christensen](https://reader036.vdocuments.net/reader036/viewer/2022062806/5697bf8c1a28abf838c8b70f/html5/thumbnails/1.jpg)
Ecosystem-scale optimization policiesEcosystem-scale optimization policies
IncoFish EwE Workshop,
Cape Town, September 2006
IncoFish EwE Workshop,
Cape Town, September 2006
Villy Christensen
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Optimum fishing policyOptimum 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.
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.
![Page 3: Ecosystem-scale optimization policies IncoFish EwE Workshop, Cape Town, September 2006 IncoFish EwE Workshop, Cape Town, September 2006 Villy Christensen](https://reader036.vdocuments.net/reader036/viewer/2022062806/5697bf8c1a28abf838c8b70f/html5/thumbnails/3.jpg)
• 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)
• 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)
Policy objectivesPolicy objectives
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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.
• 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.
![Page 5: Ecosystem-scale optimization policies IncoFish EwE Workshop, Cape Town, September 2006 IncoFish EwE Workshop, Cape Town, September 2006 Villy Christensen](https://reader036.vdocuments.net/reader036/viewer/2022062806/5697bf8c1a28abf838c8b70f/html5/thumbnails/5.jpg)
Optimizing social benefits
1 Social benefits are expressed through the
employment supported by each fleet;
2 The benefits are calculated as
fleet specific jobs/value of catch;
1 Social benefits are expressed through the
employment supported by each fleet;
2 The benefits are calculated as
fleet specific jobs/value of catch;
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Mandated rebuildingMandated rebuilding1 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;
2 In Ecosim: set a threshold biomass, and optimize towards the fleet effort structure that will ensure this objective;
1 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;
2 In Ecosim: set a threshold biomass, and optimize towards the fleet effort structure that will ensure this objective;
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Maximizing ecosystem structure Maximizing ecosystem structure
1 The ‘ecosystem structure’ definition is inspired
by Odum’s description of ecosystem ‘maturity’
wherein mature ecosystems are dominated by
large, long-lived organisms;
2 The group-specific biomass/production ratio
provides the default weighting factor for the
maximization of overall biomass;
1 The ‘ecosystem structure’ definition is inspired
by Odum’s description of ecosystem ‘maturity’
wherein mature ecosystems are dominated by
large, long-lived organisms;
2 The group-specific biomass/production ratio
provides the default weighting factor for the
maximization of overall biomass;
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Balancing objectives: Pauly’s favorite Balancing objectives: Pauly’s favorite
1 lost leg
1 war
2 wives
+1 ulcer
=5
1 lost leg
1 war
2 wives
+1 ulcer
=5
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Balancing objectivesBalancing 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.
• Society as sole agent
• 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.
• Society as sole agent
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Single- & Multi-agentsSingle- & Multi-agents
• Up to now we have assumed that society serves as sole-owner of the resources;
• More often there are multiple stakeholders whose privileges have to be considered;
• Such multi-agent considerations are incorporated by optimizing for each fleet individually
• Up to now we have assumed that society serves as sole-owner of the resources;
• More often there are multiple stakeholders whose privileges have to be considered;
• Such multi-agent considerations are incorporated by optimizing for each fleet individually
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Optimizing for profit
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Optimizing jobs
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Biomass diversity
0.0 0.2 0.4 0.6 0.8 1.0
Weight placed on profit, jobs or ecology
0.6
0.8
1.0
1.2
1.4
1.6
Div
ers
ity in
de
x
Ecology
Profit
Jobs
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Optimizing profits & jobsProfits Jobs (value) Ecology
Diversity TL of catch Catch weight
Wei
ght o
n jo
bs
Weight on profits
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Optimizing profits & ecologyProfits Jobs (value) Ecology
Diversity TL of catch Catch weight
Wei
ght o
n ec
olog
y
Weight on profits
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Optimizing ecology and jobsProfits Jobs (value) Ecology
Diversity TL of catch Catch weight
Weight on ecology
Wei
ght o
n jo
bs
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Guidelines
• Fit the model to time series data first – Without it we have no way of knowing if the
model is realistic
• Consider what time period to search over– Historic?– Forward, leaving fishing as in time series?
• Repeat the simulations using random start values
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Conclusions
• Unrealistic model unrealistic run• There can be weightings that improve the
situation for all objectives• There may be fleets loosing out
• Unrealistic model unrealistic run• There can be weightings that improve the
situation for all objectives• There may be fleets loosing out