BIOMAS: A bio-economic modelling and assessment system for fisheries management strategy evaluation

Abstract

Listen

Translate article

The primary goal of data collection on exploited fish stocks is to enable the development of credible stock assessments. Ideally, enough information will be collected to enable management strategy evaluations on the stock, providing guidance on future management decisions. In many fisheries management agencies, however, the ability to rapidly and cost-effectively build and run models to evaluate management strategies is as much an impediment to their development as the lack of data.The BIOMAS software provides users with the ability to rapidly develop single or multi-species, length-based population dynamics models for the exploration of alternative management strategies in a Bayesian-based framework. The system is theoretically capable of incorporating any number of species, fishing fleets and spatial compartments in a single model. Further complexity is provided with the ability to implement management and environmental effects on stocks as well as the tracking of economic costs and revenue from fishing activity. However, in practice model complexity will be limited by the needs of the modelling project, by the availability of data and by the modelling project timeline.By incorporating Bayesian methods, including prior probability distributions, the BIOMAS system enables users to explore the uncertainty surrounding a limited number of parameter values and to incorporate this uncertainty into the model results. Sensitivity analyses can be run against virtually all model parameters providing insight into the key drivers for the model and likely candidates for Bayesian priors. A number of management indicators are provided for all stocks and fleets in the model including stock depletion, catch weights, age- and length-frequencies, discard mortality estimates and fleet profits – each with Bayesian-based confidence intervals. Such indicators become the primary means of comparing the effectiveness of alternative management strategies when using the system forecasting capabilities. Through the inclusion of stochastic processes, such as process error and environmental and pricing fluctuations, each management strategy can also be evaluated for its robustness to such uncertainty.The ability to reflect more of our uncertainty in modelled outcomes, which tools such as BIOMAS provide, can unfortunately come at the expense of clarity in the outcomes. This is only because these models better encompass our lack of knowledge about fishery systems. Fortunately, such modelling tools can also provide us with a clearer understanding of the main sources of this uncertainty. Furthermore, the unique design of the BIOMAS system allows users to undertake ‘research strategy evaluations’ in which the costs and benefits of different forms of research can be compared, allowing managers and research leaders to see more clearly the benefits of targeted research to reduce these uncertainties.