CPUE standardization for swordfish (Xiphias gladius) by Japanese longline fishery in the Indian Ocean using zero-inflated Bayesian hierarchical spatial model

Standardization of swordfish CPUEs (1979-1993, 1994-2022) in the Indian Ocean by Japanese longliners was conducted for the datasets in four areas (NW, NE, SW, SE). We applied Bayesian hierarchical spatial models. Since the catch data include many zeros, we evaluated zero-inflated Poisson GLMM (ZIP-GLMM). Best candidate model was selected based on Widely Applicable Bayesian Information Criterion (WAIC). From the lowest value of WAIC, spatial Poisson GLMM with autoregressive (AR1) modelled for the year trend (i.e. m_zip_spde2 model) was selected as the best candidate for each area except for SE area. The trends of CPUEs were generally similar among areas with slight differences.