Stock assessment of the western winter-spring cohort of Ommastrephes bartramii in the Northwest Pacific Ocean using a Bayesian hierarchical DeLury model based on daily natural mortality during 2005-2015
Qi Ding, Jie Cao, Xinjun Chen

The purpose of this study was to evaluate the effect of the intensive commercial jigging fishery on the western winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean and to estimate the exploitation status of this stock during the period 2005-2015. We applied a Bayesian hierarchical DeLury depletion model to the Chinese jigging fisheries data to estimate the stock abundance and catchability for each year, and sensitivity analysis on daily natural mortality (M) was conducted. The results indicated that M values had great impacts on the overall estimates of stock size. Initial annual population sizes varied from 66 to 662 million individuals with the M value of 0.003-0.01 per day during the study period. O. bartramii suffered from a certain degree of overexploitation in 2008. The proportional escapement values (M=0.003-0.01) were 8.94% to 19.82% in 2008, with an average of 13.74%, which may have led to a low abundance of O. bartramii and annual catch since 2009. As short-lived ecological opportunists, O. bartramii are extremely sensitive to changes in multi-scale environmental conditions, especially when anomalous environmental conditions occur, and significant between-year variations in the initial abundance resulted in O. bartramii suffering from a certain degree of overexploitation in 2010. Although the proportional escapement met the management target of 40% from 2011 to 2015, the stock size and annual catch still fluctuated at relatively low levels. Improved knowledge of the influences of environmental conditions on abundance of the western winter-spring cohort of neon flying squid can contribute to the sustainable management of this stock.

Keywords: Ommastrephes bartramii; daily natural mortality; Bayesian hierarchical DeLury depletion model; stock assessment; Northwest Pacific Ocean
Contents of this volume Sci. Mar. 83(2) : 155-166 Back PDF
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