Using Fuzzy Synthesis Approach to Extract Fishing Efforts Directed on Albacore for Taiwanese Longline Fleets in the Indian Ocean

Abstract

Indian albacore fishery is one of the most important tuna fisheries for Taiwanese long-line fleets. The assessment of the Indian albacore stock is usually based on fishery-dependent data submitted from Taiwanese longline vessels. Moreover, those fishery data may contain two fishing types that are able to make standardizing catch per unit effort difficult. Therefore, in the present study, an alternative approach of fuzzy synthesis clustering is used to partition the fishing efforts from different fishing types, and the daily set catch information of logbooks from 1979 to 1997 is used as the fundamental data for this purpose. A fuzzy transformation is composed of weighting vector and membership function, in which the weighting vector used an unequal crisp value and the membership function used the distribution of percent catch of albacore in total of albacore, bigeye tuna, and yellowf in tuna under the factors of vessels' tonnage categories, fishing area, the number of hooks used and sea surface temperature. Subsequently, the result is obtained from the computation of fuzzy transformation, then, new catch, fishing effort and catch per unit effort series were obtained. The fuzzy synthesis is evidenced as on of the methods using for partitioning fishing efforts from different fishing types in preliminary.