STANDARDIZED CATCH RATES OF YELLOWFIN (Thunnus albacares) CAUGHT BY THE BRAZILIAN FLEET (1978-2012) USING GENERALIZED LINEAR MIXED MODELS (GLMM) USING DELTA LOG APPROACH

Catch and effort information from the Brazilian tuna longline fleet (national and chartered) in the equatorial and Southwestern Atlantic Ocean was collected. During the period from 1978 to 2012 75,195 sets were analyzed. The CPUE of yellowfin tuna was standardized by a Generalized Linear Mixed Models (GLMM) using a Delta Lognormal approach. The factors used in the model were: quarter, year, area, and fishing strategy. The standardized CPUE series shows a significant oscillation over time, with a general increasing trend from the final of the eighties to 1998, then a sharp decrease from that year on.

Stock assessments for large pelagic are commonly based on catch per unit of effort (CPUE) due to the greater availability of such data. Although CPUE has been classically used as an index of relative abundance, the relationship between the CPUE and the actual abundance is not linear, being affected by several factors, which may, therefore, lead to interpretation errors and make its utilization rather complex. As a result of market changes over the years, for instance, a number of fleets have frequently altered their fishing strategies in order to increase their efficiency. Since 1956, when longline fishing operations began in the Southern Atlantic Ocean, a number of changes in fishing operations and strategies have been observed which directly reflect on catch compositions (Amorim e Arfelli, 1984; Hazin et al., 2007; Carvalho et al., 2010; Mourato et al., 2011). Such variations lead to oscillations in catchability which may introduce serious errors in the estimation of abundance indices. The incorporation of these factors in the estimation of CPUE is, therefore, crucial for accurate stock assessments. The main objective of the present paper was, thus, to update a standardized CPUE series for albacore tuna caught by Brazilian longliners in the Atlantic Ocean, which may be utilized in the next albacore stock assessment, scheduled for April, 2016.

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