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Xu Luoliang, Chen Xinjun, Wang Jintao, Guan Wenjiang. Stock assessment and management of Dosidicus gigas in the Southeast Pacific Ocean with Schaefer model[J]. Haiyang Xuebao, 2015, 37(10): 49-58. doi: 10.3969/j.issn.0253-4193.2015.10.005
Citation: Xu Luoliang, Chen Xinjun, Wang Jintao, Guan Wenjiang. Stock assessment and management of Dosidicus gigas in the Southeast Pacific Ocean with Schaefer model[J]. Haiyang Xuebao, 2015, 37(10): 49-58. doi: 10.3969/j.issn.0253-4193.2015.10.005

Stock assessment and management of Dosidicus gigas in the Southeast Pacific Ocean with Schaefer model

doi: 10.3969/j.issn.0253-4193.2015.10.005
  • Received Date: 2015-04-04
  • Dosidicus gigas is one of the important economic cephalopod in the world. It is widely distributed in the east of Pacific Ocean. Nowadays the yield of Dosidicus gigas occupies more than 50% of the total yield of squid in China mainland. In 2012 ,the yearly catch in China mainland reached 221.1 thousand tons,the number of fishing vessels are more than 250. It is necessary to assess the stock for making the fishery sustainable. Unfortunately little work is done in this field.The stock assessment and risk analysis of alternative management strategies for Dosidicus gigas in the Southeast Pacific Ocean were carried out by using a Bayesian Schaefer model,in which two scenarios,standard scenario and sensitivity analysis scenario,are considered.The Schaefer model was chosen because of the lack of age-data of Dosidicus gigas and also because the migration mechanism and stock structure of the squid was very complex which was not completely understood by us. In many cases,Schaefer model performed better than many other more complex models such as age-data based models or metapopulation model. For parameters K and q in standard scenario,the posterior distribution are approximately normal distributed. It is totally different with the prior distribution which is set to be uniform distribution. Compared with the two scenarios,the results of posterior distribution of the three parameters are similar .The study indicated that the data of yearly yield and CPUE provided sufficient information for the valuation of model parameters. Under standard scenario,the MSY (maximum sustainable yield)is 1.429 million tons. To maintain MSY,the biomass and fishing mortality should be 2.147 million tons and 0.682,respectively. Under sensitivity analysis scenario,the MSY is 1.525 million tons. To maintain MSY,the biomass and fishing mortality should be 2.296 million tons and 0.691,respectively. Under both scenarios,the fishing mortalities and yearly catches from 2003 to 2012 were lower than reference points F0.1 and MSY,and the biomass was greater than target reference point Bmsy. Status of resource was good and it was not suffering overexploiting or exploited. We set 7 indexes to evaluate alternative strategies and simulated 1 000 times for every single harvest rates from 0.1 to 0.8. Strategy and risk analysis indicated that when the harvest rate was up to 0.7,the average yearly catches would be decreasing. And when the harvest rate was set below 0.3,the resource could be well protected and the probability of resource collapse would be very low. It is concluded that the harvest rate of 0.3 appears to be the best management regulation and the MSY will attain at 990 thousand tons. The harvest rate from 2003 to 2012 were all below 0.3,it was a reason for us to be optimistic for this potential resource. However there were many uncertainty factors in the simulation which should be considered in future studies.
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