Bioeconomic evaluation of fisheries enforcement effort using a multifleet simulation model

The economics of enforcement is traditionally modelled using rational agents assumed to act according to their expected economic utility. In this investigation we derive this expectation by implementing a stochastic simulation model to integrate across associated levels of uncertainty using Monte Carlo. The model is developed for the South Georgia toothfish longline fishery, in which legal catches are strictly managed according to the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) conservation measures. Assuming full compliance in the legal fishery, this investigation deals with the role of a fishing patrol vessel (FPV) in excluding illegal fishing vessels. Both legal and illegal fleets are dynamic. For the legal fleet, catch is set by a harvest control rule within the model framework, with vessels leaving if fishing becomes unprofitable. The illegal catch is determined by the number of vessels operating, which predicts catch on the basis of an estimated production function. The exit of illegal vessels is determined by the probability of detection by the FPV, which is a function of days spent on patrol, and estimated profits. The entry of illegal vessels occurs at a fixed mean rate, with the model integrating over uncertainty in this parameter. An obvious trade off exists in that higher levels of illegal activity lead to lower expected returns to the legal fleet. We thus provide a cost-benefit framework for investigating the trade-offs associated with decisions on enforcement in the fishery, and confirm that current enforcement effort levels are well justified.