FISMO: A Readily Generalized Fisheries Simulation

FISMO: A Readily Generalized Fisheries Simulation

Ernesto A. Chávez

FISMO: A Readily Generalized Fisheries SimulationThis is part of Fisheries Assessment and Management in Data-Limited Situations
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Assessing tropical fisheries is often problematic due to the fact that the population parameters of natural stocks are poorly understood or unknown. Even when there is evidence of stock depletion (e.g., reduced catch and declining abundance) occurring within the fishery, accurate diagnosis and assessment of actual stock condition is difficult or impossible. Therefore, a semi-automated, age-structured simulation model (FISMO) was developed to allow reconstruction of the age structure and population size of a fishery to assess the stock and some important reference points useful for decision-making and management. The model carries out assessments using parameter values of targeted, or similar, stocks that are available in FishBase and catch records from the FAO Web site. Reconstruction of cohorts is made as numbers and biomass per age group. The number of age groups explicitly considered is limited to 20. Population parameter values (growth rate, length weight, age at maturity, age at first catch [tc], catchability), total catch value, costs of fishing operations, number of fishing days per year, fleet size, and 15 years of catch data are used as input. The model also estimates natural mortality, longevity, φ, asymptotic weight, the benefit/cost ratio, and total profits. The stock-recruitment relationship is determined so that simulated cohorts can be linked over time and, using the yield equation, the model estimates fishing mortality (F) for each year. Yield and profits are simulated by assuming that tc and fishing gear selectivity patterns have remained unchanged over time. Graphic displays allow identification of biological and economic optimum yields as a function of F and tc. The model fits recorded catch, and then simulated yields and profits as functions of F and tc (both chosen by the user) are model outputs and can be used as an interactive management tool. This model version can be applied to most exploited stocks and can be modified for particular cases.

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