2019 updates of stock assessment for Pacific saury in the North Pacific Ocean by using Bayesian state-space production models

Stock assessment for the North Pacific saury was conducted based on the new specification (2 base cases and 4 sensitivity cases) agreed in the 5th SSC-PS meeting held in November 2019. The basic model employed in the analysis was the state-space surplus production model as agreed in the SSC-PS01 as an interim stock assessment model. The model can account for process and observation errors in the abundance indices.  Parameters in the models were estimated based on Bayesian framework with a Markov chain Monte Carlo method. The estimation results were diagnosed with respect to shapes of posterior distributions, residual plots, retrospective pattern and predictability of the future population status. The outcomes of stock status and future projection were shown according to the template agreed in the 5th SSC-PS meeting. 
As for the base case stock assessment result, the 2019 median depletion level was only 26% of the carrying capacity (80%CI=16.8-37.1%), declined from 33.9% (80%CI=22.2-47.7%) in 2018. Furthermore, B-ratio (=B/Bmsy) in 2019 and F-ratio (=F/Fmsy) in 2018 were 0.574 (80%CI=0.383-0.837) and 1.382 (80%CI=0.901-1.958), respectively. In addition, the probability of the population being in the green Kobe quadrant in 2018 was estimated to be less than 10%, while the probability of being in the red Kobe quadrant was assessed to be greater than 80%, which indicated that the population was overfished and subject to overfishing in 2018. 
For population outlook, population dynamics were projected for some scenarios with respect to several levels of reduction/increase of catch as well as status quo. The results showed that continuation of the current level of catch may cause a further decline in the population size. However, as shown in the retrospective/hindcasting analyses, the estimation for the recent population size tended to depend on the recent data set. Therefore, for providing better management advice, the authors strongly suggest that the analysis should be updated using the most recent abundance indices  (including 2020 fishery-independent abundance index and 2019 CPUE indices).