Zusammenfassung: A dynamic model for open-access fisheries is presented. In addition to density dependence in recruitment and fishing effort changing in proportion to the level of profit fishermen earn which characterizes previous open-access models, it incorporates full age structure for the fish stock, lognormal environmental recruitment variability, and gear selectivity. The predator-prey cycling solution of the original Schaefer dynamic model, and subsequent open-access models, persists for these model extensions. Density dependence in recruitment induces greater global stability. Environmental recruitment variability, common in marine populations, is destabilizing in the neighborhood of the open-access equilibrium. Approximating model steady states of effort and catch by the corresponding averages from data time series underlies a new algorithm of parameter evaluation, applied here to an open-access model of the Georges Bank sea scallop (Placopecten magellanicus) fishery.

Zusammenfassung: The algorithm discribed shares with the gradient methods their ability to converge from an initial guess which may be outside the region of convergence of other methods. The algorithm shares with the Taylor series method the ability to close in on the converged values rapidly after the vicinity of the converged values has been reached. Thus, the method combines the best feutures of ith predecessors while avoiding their most serious limitations.

Zusammenfassung: The statistical model for the Petersen method is a hypergeometric distribution. Approximation to a binomial distribution has been used, and the usual method for this binomial model is based on approximation to a normal distribution. The Bayesian statistical model for a binomial distribution, which assumes that the prior distribution of parameters is uniform, corresponds well with the conventional method. However, the Bayesian statistical method for a hypergeometric distribution which assumes the uniform prior distribution is not feasible. The prior distribution according to the inverse squared parameter is natural for this model. Beta function and zeta function are important to understand these methods. This model is simpler to understand and easier to calculate by micro-computer than the conventional method.