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¹ Research Institute for Tuna Fisheries, Bali, Indonesia
² Forestry and Fisheries (DEFF), Department of Environment, Cape Town, South Africa
³ University of Cape Town, Department of Biological Sciences, Cape Town, South Africa
⁴ National Taiwan Ocean University, Department of Environmental Biology and Fisheries Science, National Taiwan Ocean University, Keelung, Taiwan DOI : 10.4194/TRJFAS19142 Viewed : 1021 - Downloaded : 890 The present study aimed to determine the abundance index of blue marlin, Makaira nigricans (Lacepède, 1802) utilizing fishery-independent data, i.e., scientific observer, and attempted to bridge the research's gap for low coverage information in the northeastern Indian Ocean. A total of 2,984 set-by-set observer data from 2006-2018, spatially disaggregated by one-degree blocks, were obtained from the Indonesian scientific observer program following commercial longline fleets. A delta-lognormal model was chosen to fit the dataset, using catch as the response variable with seven covariates. A backward procedure based on AIC, BIC and R2 were used to select the best model. Overall, the delta-Gamma performs better when modelling data with a high proportion of zeros than other traditional models. The blue marlin CPUE trend is relatively stable over time, despite the inter-annual fluctuations, which are likely a result of natural variation in the population as opposed to operational changes or inter-annual environmental variation. Given the low spatial coverage compared to logbook data, scientific observer data performed well and produced a robust abundance index of blue marlin in the northeastern Indian Ocean. Keywords : Logbook, Scientific observer, Billfish, Catch and effort, By-catch