Fisheries biologists have at their disposal today a number of programs and software packages, specially for IBM-PC compatibles, that perform virtual population analysis or other analysis normally used in population dynamics (Sims, 1985; Hightower, 1986; Sparre, 1987; Gayanilo et al.,1988; Mesnil, 1988). Other unpublished programs also exist in places where population dynamics work is carried out. For some fisheries, however, it is impossible to obtain all of the necessary data to run one of these programs (generally the catch matrix in numbers of individuals by age and year is required). In such fisheries the scientist is confronted with the choice of waiting to have a sufficiently long time series to, in the future, apply the above mentioned methods or try to use the existing data to say something about the population under study. Many times, the scientist is also obliged to advise fishery managers that, needless to say, cannot wait to take decisions.
In order to carry out these calculations of the dynamics of the population it is necessary to work with restrictive hypotheses and the errors associated with them. When long time series are not available, the first hypothesis that has to be used is that of steady state or equilibrium. That means assuming that the size structure of the stock is identical to that of each and everyone of its cohorts, thus referring to pseudocohorts instead of cohorts. Obviously, we are talking about a restrictive hypothesis because, in general, the population is not in equilibrium given that neither the recruiting nor the mortality are a constant. Knowing the errors associated with accepting such hypotheses does not eliminate them, but it allows to make an adequate interpretation of the results and can produce an objective assessment of the studied population.
