A comparative multi-fleet analysis of socio-economic indicators for fishery management in SE Brazil

Abstract

One of the problems in an ecosystem approach to fisheries management is the lack of economic analyses which clearly define the performance of different fishing fleets within the system. We describe a comparative multi-fleet analysis of socio-economic indicators applicable for inclusion into ecosystem modeling and management. Based on a survey of different industrial fishing fleets in São Paulo, Southeastern Brazil, an inter-fleet comparison of economic attributes such as investment, fixed costs, effort, labour, sailing-related costs and profits, as well as a set of performance indicators, was conducted. Costs varied between fleets with fuel being the largest component on average, representing almost 37% of total costs. Similarities between fleets were driven by fuel costs, gross incomes and profits. In general, the best economic performance was associated with indicators of profitability and economic efficiency. Bottom-longliners and both surface and bottom-gillnet fleets showed the best economic performance per fishing trip due to their low percentage of variable costs. Purse-seiners and pink-shrimp trawlers had the lowest average rate of return and economic efficiency because of their high variable costs and relatively low catch values, and were considered economically net losers. However, in terms of jobs generated, purse-seiners had the greatest value creating about 49% of total jobs by all fleets. The sea-bob-shrimp fleet had the lowest crew size per vessel but generated the second highest total number of direct jobs (23%), with high economic viability as a whole. The inter-fleet cost and socio-economic performance analysis revealed that additional attention should be given to the poor profitability and overcapacity of fleets, fishing impacts, and open-access related issues, while social indicators may also be considered. This study provides information useful for evaluating different fisheries management scenarios and fleet size optimization in the South Brazil Bight, for ecosystem modeling policy optimization routines, and for a pragmatic ecosystem approach to fisheries management.