Impact Factor: 0.482
​5-Year Impact Factor: ​0.764
Journal Citation Reports® 2017
Related Journals
Related Journals
Turkish Journal of Fisheries and Aquatic Sciences 2019, Vol 19, Num, 2     (Pages: 119-129)

Standardization of Catch Per Unit Effort with High Proportion of Zero Catches: An Application to Black Marlin Istiompax indica (Cuvier, 1832) Caught by The Indonesian Tuna Longline Fleet in The Eastern Indian Ocean

Bram Setyadji 1 ,Humber Agnelli Andrade 2 ,Craig Hutton Proctor 3

1 Research Institute for Tuna Fisheries, Bali, Indonesia
2 Federal Rural University of Pernambuco, Recife, Brazil
3 Commonwealth Science and Industrial Research Organisation, Marine and Atmospheric Research, Hobart, Tasmania, Australia
DOI : 10.4194/1303-2712-v19_2_04 Viewed : 742 - Downloaded : 556 Black marlin (Istiompax indica) is a bycatch species in the Indonesian tuna longline fishery operating in the eastern Indian Ocean. Approximately 18% (~2,500 tons) of black marlin caught in the Indian Ocean are landed in Indonesia. However, its population status in the Eastern Indian Ocean is still little known. In this present study, a Generalized Linear Model (GLM) was used to standardize the catch per unit effort (CPUE) and to estimate relative abundance indices based on the Indonesian longline dataset. Data was collected by scientific observers from August 2005 to December 2014. Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to select the best models among all those evaluated. If using the AIC, negative binomial (NB) and zero-inflated negative binomial (ZINB) models were selected, but if using BIC, the NB model was the best option. Time trends of standardized CPUE, as calculated using NB and ZINB models, were similar from 2008 onward. However, the trends were conflictive in the early stages of the series (2005-2007). A principal outcome is that there was no strong motivation to choose one of the two models, NB or ZINB), over the other. Sensitivity analyses are recommended as the alternative when running stock assessment models using such time series. Keywords : Relative abundance, By-catch, Stock assessment, Generalized Linear Model