Skipjack tuna is targeted by various types of fishing gear in coastal countries. Due to itsresilience, it has withstood heavy fishing pressure in the past few decades. Coastal drifting gillnetfleets also mark skipjack as their main target, but it is often overlooked in terms of stock assessment.This study provides new information on an abundance index based on fishery-dependent data from2010 to 2017. Generalized linear models (GLMs) were used to standardize the catch-per-unit-ofeffort(CPUE) using year, quarter, and gross tonnage as the prediction variables. Model goodnessof-fit and model selection were based on the Akaike Information Criterion (AIC), the pseudocoefficient of determination (R2), and model diagnostics with a residual analysis. The finalestimation of the abundance index was calculated by least square means or marginal means. Theresults showed that the index was heavily influenced by the year and quarter, but it did not relateto the vessel’s capacity. While the CPUE series fluctuated greatly, it showed a declining trend overthe years of observation.

Skipjack tuna supports a valuable commercial fishery in Indonesia. Skipjack tuna are exploited in the Indian and Pacific Oceans with a variety of gear but drifting gillnets are a common method used by Indonesian fishers. However, despite of its importance, little information on the drifting gillnet fishery is available. This study describes a preliminary examination of the catch and effort data from the Indonesian skipjack drifting gillnet fishery. Utilizing daily landing report from 2010-2015, nominal catch per unit of effort (CPUE) data were calculated as kg/day at sea. Generalized Linear Models (GLM) were used to standardize the CPUE, using year, quarter, day at sea, and area as fixed variables. Model Goodness-of-fit and model comparison was carried out with the Akaike Information Criteria (AIC), the pseudo coefficient of determination (R2) and model validation with a residual analysis. The final estimation of abundance indices was calculated by least square means (LSMeans) or Marginal Means. The results showed that days accounted for most of the variation in CPUE, followed by year, quarter, and area. In general, there were no noticeable trends indicative of over exploitation or population depletion suggesting a sustainable fishery for Skipjack tuna in Indonesian waters.