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Overfishing of bigeye tuna in the eastern Pacific Ocean has motivated a search for a practical means of reducing the catch of bigeye tuna in mixed species aggregations. To explore the effects of gear characteristics on the catch of bigeye tuna, a classification algorithm for the presence/absence of bigeye tuna catch in purse-seine sets on floating objects is developed, using the tree-based method, random forests. Although the location of the set was the strongest determinant of bigeye tuna catch with these data, bigeye tuna in some areas were more likely to be caught on floating objects with greater underwater depths and with deeper purse-seines. Misclassified sets that caught bigeye tuna were concentrated within certain vessels, suggesting the existence of additional vessel effects. Results indicate that fishers may avoid catching bigeye tuna in some areas by changing the depth of the material hanging from the floating object and the actual fishing depth of the purse-seine, or by moving to other fishing areas. Nonetheless, given the complexity of configuring a purse-seine, and the difficulties associated with monitoring compliance with gear regulations, fishery-wide gear restrictions would be problematic.

Effects of gear characteristics on the presence of bigeye tuna (Thunnus obesus) in the catches of the purse-seine fishery of the eastern Pacific Ocean