On the dynamics of commercial fishing and parameter identification

Abstract

This paper has two main objectives. The first is to develop a dynamic model of commercial fisheries different from most existing models that assume optimizing behavior. The industry is assumed to have a well-defined index of performance based upon which the decision to invest or not is made. We do not, however, assume that the industry or firm is efficient or optimal in its operations. The second is that a new approach of fitting model dynamics to time series data is employed to simultaneously estimate the poorly known initial conditions and parameters of nonlinear fisheries dynamics. The approach is a data assimilation technique known as the variational adjoint method. Estimation of the poorly known initial conditions is one of the attractive features of the variational adjoint method.