Ecosystem-scale optimization policies IncoFish EwE Workshop, Cape Town, September 2006 IncoFish EwE Workshop, Cape Town, September 2006 Villy Christensen

Optimum fishing policy Ecosim ( provides formal optimization methods to search for fishing policies that would maximize a particular policy goal or ‘objective function’ for management.

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 objectives

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.

Optimizing social benefits 1 Social benefits are expressed through the employment supported by each fleet; 2The benefits are calculated as fleet specific jobs/value of catch; 1 Social benefits are expressed through the employment supported by each fleet; 2The benefits are calculated as fleet specific jobs/value of catch;

Mandated rebuilding 1External pressure (or legal decisions) may force policy makers to concentrate on preserving or rebuilding the population of a given species in a given area; 2In Ecosim: set a threshold biomass, and optimize towards the fleet effort structure that will ensure this objective; 1External pressure (or legal decisions) may force policy makers to concentrate on preserving or rebuilding the population of a given species in a given area; 2In Ecosim: set a threshold biomass, and optimize towards the fleet effort structure that will ensure this objective;

Maximizing ecosystem structure 1The ‘ecosystem structure’ definition is inspired by Odum’s description of ecosystem ‘maturity’ wherein mature ecosystems are dominated by large, long-lived organisms; 2The group-specific biomass/production ratio provides the default weighting factor for the maximization of overall biomass; 1The ‘ecosystem structure’ definition is inspired by Odum’s description of ecosystem ‘maturity’ wherein mature ecosystems are dominated by large, long-lived organisms; 2The group-specific biomass/production ratio provides the default weighting factor for the maximization of overall biomass;

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

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. 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

Single- & 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

Optimizing for profit

Optimizing jobs

Biomass diversity

Optimizing profits & jobs ProfitsJobs (value)Ecology DiversityTL of catchCatch weight Weight on jobs Weight on profits

Optimizing profits & ecology ProfitsJobs (value)Ecology DiversityTL of catchCatch weight Weight on ecology Weight on profits

Optimizing ecology and jobs ProfitsJobs (value)Ecology DiversityTL of catchCatch weight Weight on ecology Weight on jobs

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

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