Stock Assessment Of Bigeye Tuna (Thunnus Obesus) In The Indian Ocean

Bigeye tuna?Thunnus obesus?,a highly migratory species,is widely distributed in the tropical and subtropical waters of the Pacific,Atlantic and Indian Ocean,which is managed by the Regional Fisheries Management Organizations.Bigeye tuna is also an important target species in Chinese longlines fishery in the distant water,whose research and sustainable exploitation are concerned by both scientists and government managers.Therefore,based on the data from the Indian Ocean Tuna Commission?IOTC?website and the logbook data of China's longline fisheries,this paper make stock assessment for bigeye tuna in Indian Ocean,and standardize the CPUE of Chinese longline fisheries,considering various uncertainties.The main research contents and results are as follows:?1?Based on the catch from 1950 to 2016 and Catch Per Unit Effort CPUE from1955 to 2016,the stock of the Indian Ocean bigeye tuna was assessed by the Bayesian state space surplus production model in an open environment,JABBA?Just Another Bayesian Biomass Assessment?,explored the implications on the effects of fishing boat and CPUE scale.The results showed that the stock assessment was sensitive to different CPUE,and the scenario using CPUE considering vessel effect from 1979 to 2016 was revealed to perform best with the lowest Root-Mean-Squared-Error?RMSE?and Deviance Information Criterion?DIC?,and selected to be the base case.The median estimate for bigeye tuna biomass in 2016 was 812 kt,and the Maximum Sustainable Yield?MSY?was estimated to be 163 kt,which was much higher than the catch?86.81 kt?in2016,indicating that the stock was not overfished,with 81%in the green zone of the Kobe plot.The biomass of bigeye tuna would be higher than the biomass that can produce the maximum sustainable yield(B_MSY)in the next 10-year projection when the total permissible catch was set to 69.45-104.17 kt?80-120%of catch in 2016?.There were some retrospective errors in the stock assessment results,with underestimated fishing rate and overestimated biomass.Therefore,the stock assessments should be improved by updating the model structure,CPUE standardization,and prior distribution of model parameters setting.?2?Bigeye tuna is an important target fish in China's ocean longline fisheries,whose CPUE is influenced by the fishing technique,and various environmental factors.Therefore,based on 2014-2018 China's longline fishery data in the Indian Ocean and environmental data?sea surface temperature,chlorophyll,etc.?on the Ocean Watch website,this paper constructed Generalized Addictive Model?GAM?to standardize CPUE for Chinese bigeye tuna fishery in the Indian Ocean.All significance variables were added to the GAM model one by one,and the best standardization model was selected according to AIC?Akaike Information Criterion?.The results show that there are7 significant variables,which are year,month,fishing boat,longitude,latitude,and sea surface temperature?SST?,and the annual with longitude interaction terms.The GAM model which the maximum deviance explained for CPUE was 26.9%.Above these significant variables,the year and month variables have a greater impact on CPUE,explaining the total deviations of 8.13%and 7.97%,respectively.Higher CPUE occurs between 40°E-60°E and 15°S-10°S.In the temperature range of 24?-32?,the overall change trend of CPUE is large,When SST is in the range of 24?-32?,its catch level is high.This result may be that bigeye tuna likes warm waters,so it is rare in low temperature seas.?3?In the process of stock assessment,standardized CPUE is used to reflect changes of stock abundance,and optimizing the catchability coefficient q can reveal the fishing technique update,whose precise consumption can improve the model fitting and parameters estimation.This paper considered the standardized CPUE of China and time-varying q to update the previous stock assessment of bigeye tuna.Different scenarios were constructed to explore the influence of various CPUE in different regions and q with different increase level?i.e.constant,1%,2%,or 3%per year?.Based on the DIC and RMSE criterion,the S5 model strategy?R1?ID?7918,R2?ID?7918,and CHN?1418?is selected as the best model scenario and also the model strategy,which was finally selected as the base case model for assess the Bigeye tuna stock.Different increase level of q was considered based on the base case model scenario.The results show that B₂₀₁₈ is estimated at 625063 tons,and B_MSY is estimated at 672136 tons.The catch of bigeye tuna in 2018was reported to be 93493 tons,while the median and 95%confidence interval of MSY is estimated to be 130361?115534,176015?tons.The Indian Ocean bigeye tuna in 2018was subject to be overfishing,when the fishing mortality is less than the F_MSY(F/F_MSY<1)and the current biomass is less than the B_MSY(B/B_MSY<1).This result of stock status for bigeye tuna is consistent with that from WPTT of IOTC in 2019.