Management Strategy Evaluation For Bigeye Tuna In The Indian Ocean

Tuna support some most important fisheries in the world, of which bigeye tuna (Thunnus obesus) fishery yields the highest economic value. The Indian Ocean is the main fishing grounds for bigeye tuna. High fishing efforts and signs of overfishing and stock depletion call for an evaluation of alternative management strategies. In this study I developed a series of explicit management strategy/harvest control rules to evaluate performance of alternative management strategies for this fishery. The management strategy evaluation program developed in this study includes basic evaluation of five groups of harvest control rules (HCRs), evaluation of three appropriate HCR candidates with consistent data of updated stock assessment, and evaluation of reducing purse seine fishing effort scenarios. I simulated the population dynamics of bigeye tuna in the Indian Ocean using age-structured production model (ASPM) with biological and fishery data being obtained from the Indian Ocean Tuna Commission (IOTC) stock assessment reports. The management strategies were evaluated using various performance measures, including catch and spawning stock biomass (SSB) associated indicators. The main development and results include:(1) Based on biological and fishery data in 2004, we developed a stochastic age-structured production model as an operating model to evaluate several alternative management strategies, and conducted sensitivity analyses for the parameters quantifying recruitment dynamics. Our simulation study considers 18 simulation scenarios to evaluate the impacts of different management strategies, uncertainty in the recruitment dynamics, uncertainty associated with observation and implementation errors on management strategy evaluation. Five management strategies, constant fishing mortality, constant catch, quasi-constant catch, constant escapement and status-dependent strategies, were evaluated using the performance indicators including average catch, average spawning stock biomass, variation in catch, average fishing mortality, and lowest biomass in the management period. This study showed that (1) for constant management strategy an annual catch of 90 thousand t tended to result in a low risk of stock being overfished while obtaining a stable catch; (2) for constant fishing mortality strategy fishing mortality of 0.3 yr-1 could yield a higher catch, but might have a high probability (64%) of stock dropping below SSBmsy; and (3) for quasi-constant catch strategy an annual catch of 110 thousand t was sustainable if current SSB was higher than SSBmsy. Constant escapement and status-dependent strategies were robust under different virgin recruitment and steepness. This study also suggests that it is important to incorporate uncertainties associated with key life history, fisheries and management processes in evaluating management strategies.(2) Based on the Stock Synthesis model output in the most updated stock assessment for bigeye tuna in the Indian Ocean in 2010, our study choose its three submodels to provide input data in the operating model, covering low, medium, high productivity, and also uncertainties in the stock assessments. Management strategies considered include constant fishing mortality, constant catch and constant escapement. Two explicit management objectives were identified, one is keeping SSB above SSBmsy (spawning stock biomass that can achieve MSY), and the other is sustainable harvesting at 0.8MSYto MSY (Maximum Sustainable Yield). The results showed that the most optimal scenarios in each management strategy are CF₀.4 (keeping fishing mortality at 0.4 yr-1),CC₁00000 (keeping annual catch at 100,000 tons) and CE₀.5 (keeping exploitation rate at 0.5), which could sustain mean SSB more than SSBmsy, but also obtain mean catch between 0.62MSY and 0.86MSY. Among three appropriate scenarios, keeping fishing mortality at 0.4 yr-1 could achieve highest catch at 0.86MSY, while scenario CE₀.5 could sustain highest biomass, meanwhile its mean catch is only 0.05MSY less than that of scenario CF₀.4. However, catch variance of scenario CE₀.5 is very high, while keeping annual catch at 100,000 tons will cause stock decline quickly, in contrast, scenario CF₀.4 could sustainably exploit this resource.(3) Using the developed management strategy evaluation framework, we evaluated constant fishing mortality and quasi-constant fishing mortality management control rules to reduce fishing effort of purse seine with fish aggregating devices (FADs) including scenarios of reducing purse seine fishing mortality quickly or gradually and transferring its fishing effort to longline fishery. The results showed that mean SSB and catch would be higher if fishing effort of purse seine with FAD could be reduced greatly and quickly. When banning purse seine with FAD (scenario PSLS₀), mean catch and catch in the last simulation year (2034) were 0.95MSY and 1.03MSY respectively, which is higher than that of basic case (scenario PSLS₁) at 0.89MSY and 0.9MSY, the mean SSB of scenario PSLS₀ was also 0.26SSBmsy higher than that of base case. Similarly behavior will also achieve if annual fishing mortality of purse seine with FAD could be reduced at 20% of that in 2009. Moreover, effects of scenarios PSLS₀ (banning purse seine fishery with FAD) and PSLS₂0% (reducing 20% fishing effort of purse seine fishery with FAD annually) would be more obvious when productivity was low. According to the Kobe II strategy matrix, probabilities of achieving biomass objectives were much higher for PSLS₀ and PSLS₂0% than for the base case (scenario of keeping fishing effort at 2009 level)both in short-term, medium-term and long-term, while annual catch would be more than that for the base case in the long run.