Assessed fisheries in developing countries may be moving toward sustainability, but little is known about the sustainability of unassessed fisheries which contribute to more than 80% of global catch. In addition, although there have been stock assessments of the most economically important species, et al.
(2012) developed a method using species’ life history, catch, and fishery development data to estimate the status of thousands of unassessed fisheries worldwide. This method does not produce precise estimates for individual fisheries and therefore is not a substitute for formal assessment. It does, however, provide a method in which to estimate the statuses of previously unassessed stocks. Costello et al. found that small unassessed fisheries are in substantially worse condition than assessed fisheries, but that large unassessed fisheries may be performing nearly as well as their assessed counterparts. Of these unassessed fisheries, Costello et al. found that 18% of stocks are collapsed. —Evelyn Byer
Costello, C., Ovando, D., Hilborn, R., Gaines, S.D., Deschenes, O., Lester, S.E., 2012. Status and Solutions for the World’s Unassessed Fisheries. Science 338, 517–520.
Costello and colleagues in Santa Barbara and Seattle developed a multivariate regression approach to identify predictors of stock status (biomass/biomass for maximum sustainable yields or B/Bmsy) from assessed fisheries and used these models to estimate the status of unassessed fisheries. They coupled existing stock assessments to a database of characteristics of each unassessed fishery such as time-series of catch, fishery development, and species’ life-history traits. The approach of Costello et al. uses the same kinds of variables as stock assessments, but fundamentally differs because a structural model linking these variables to stock status are not specified and there are no indices of abundance trends. The approach captures time-series effects, and cross-sectional effects. This approach is not a substitute for formal assessment but a useful method for estimating previously unassessed stocks. To predict stock status for assessed fisheries, a regression model estimating log(B/Bmsy) was used. To predict the status of unassessed fisheries, a companion database of 7721 marine fisheries for the FAO landings database was compiled. Five approaches were used to validate model predictions including within sample validation for assessed fisheries, bias tests for fishery size and data errors, jackknife analyses, comparisons with FAO assessments, and comparisons with B/Bmsy estimates from inside and outside more than 50 marine reserves.
Costello et al. concluded with a final data set containing 1793 unassessed marine fisheries from around the world, which comprise 23% of global landings. They found that 64% of unassessed fisheries have a stock biomass less than Bmsy, almost identical to the 63% of assessed fisheries with a stock biomass less than Bmsy. They also found that 18% of unassessed stocks are already collapsed. Overall, a median B/Bmsy of 0.63 was predicted for the world’s unassessed fisheries in 2009, much lower than the median value of 0.94 from assessed fisheries in 2007. Also, unassessed fisheries in the developing world were predicted to have higher stock masses, on average, than in the developed world. Geographic locations with highest predicted B/Bmsy include the eastern Indian Ocean, southern Indonesia, and Western Australia whereas the Northwestern Atlantic has among the lowest B/Bmsy. Generally, a stark contrast existed between the statuses of assessed and unassessed stocks, even in regions known for good management (i.e. New Zealand and Alaska). These results allow globally important policy questions to be addressed, such as the large potential conservation and food benefits from improving the management of the world’s unassessed fisheries. Costello et al. also advise that although fisheries reform such as limiting entry and using individual transferable quotas has been successful in developed countries, other methods such as territorial user right fisheries, cooperatives, and co-management approaches are likely to be more successful in developing countries.