Many factors influence the dynamics of fisheries and feedback mechanisms amongst these factors are poorly understood. The ecological systems are too large and complex to conduct controlled experiments and economic adjustments to changes in fish populations defy traditional equilibrium analysis. New modelling approaches are required to identify the driving forces behind the dynamics of exploited fish populations, assess likely consequences of alternative management measures, and achieve consensus among stakeholders.
We present an interdisciplinary modelling approach that can be used easily to assess dynamic consequences of alternative assumptions for certain key biological and economic parameters, and incorporates the input of various stakeholder groups in the fishery. Contributions of scientists, economists and managers to the model can be augmented with contributions from the fisherfolk.
Our approach is illustrated by a dynamic computer model capturing the interactions of three demersal fish species on Georges Bank, namely Atlantic Cod (Gadus morhua), Haddock (Melanogramus aeglefimts) and Pollack (Pollachius virens), population sizes of which are assumed to be density-dependent for the purposes of the model and are significantly affected by management decisions. The model addresses how management measures for one species influence the population dynamics of other commercially exploited species. Various scenarios are run to explore the implications of viable management strategies under alternative assumptions on the driving forces behind complex ecological-economic processes. The analyses indicate that neither small reductions in effort nor mesh size increases are likely to prevent the further demise of the Georges Bank ground fisheries, and, in fact, stocks of the three targeted species may decline. Alternative management measures seem to be necessary to prevent collapse, and might include various strategies, such as effort controls and mesh size reductions, in conjunction with a dramatic change in fishing technology. The assessment and viability of alternative management measures in turn require that consensus is generated among stakeholders about data and models.