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This report presents a preliminary stock assessment for Indian Ocean Skipjack tuna (Katsuwona pelamis) using Stock Synthesis 3 (SS3). The assessment uses a spatially aggregated and seasonally structured model that integrates several sources of fisheries and biological data. An alternative, spatially explicit model is also considered in the final model assemble. The assessment model covers the period 1950–2019 and represents an update and revision of the 2017 assessment model with the inclusion of updated CPUE indices, and a revised fishery structure. A range of sensitivity models are presented to explore the impact of key data sets and model assumptions.
The assessment assumed the Indian Ocean skipjack tuna constitute a single spawning stock (the spatially disaggregated model partitions the stock into a western and eastern region). The assessment model defined 7 fisheries. Standardised CPUE series from Maldives Pole and line fleet 1995 – 2018 and EU associated Purse seine sets 1990 – 2019 were included in the models as relative abundance index of exploitable biomass. A newly available index based on acoustic data from echosounder buoys and an additional index based on associative dynamics of skipjack tuna with floating objects corroborate the recent trend of the Purse seine index, and the utility of these indices were examined in the assessment. Tag release and recovery data from the RTTP-IO program were included in the model to inform abundance and fishing mortality rates.
The final assessment model options correspond to a combination of model configurations, including alternative spatial structure (one-area or two-areas), alternative values of SRR steepness (0.7, 0.8, or 0.9), alternative tag mixing period (3 or 4 quarters), and the alternative values of tag weighting parameter (lambda =1 or 0.1). The model ensemble (a total of 24 models) encompass a range of stock trajectories. Estimates of stock status were combined across from the 24 models and incorporated uncertainty estimates from individual models as well as across the model ensemble.
IOTC Resolution 16/02 adopted a harvest control rule (HCR) for skipjack tuna, which recommends a annual catch limit based on a relationship between stock status (spawning biomass relative to unfished levels) and fishing intensity (exploitation rate relative to target exploitation rate), estimated from a model-based stock assessment. Therefore, this assessment reported depletion-based target reference points, including SSB40% (40% of unfished spawning biomass), F40%SSB (fishing mortality corresponding to 40% of the unfished spawning biomass), and the target yield (equilibrium catch at F40%SSB).
The overall stock status estimates do not differ substantially from the previous assessment. Biomass was estimated to have increased considerably from the historical low level in 2015. Spawning biomass in 2019 was estimated to be 45% of the unfished level. Current fishing mortality was estimated to be very close to F40%SSB (F2019/ F40%SSB = 0.98). The probability of the stock being currently in the green Kobe quadrant is estimated to be 63%. Considering the quantified uncertainty, the stock is considered not to be overfished and is not subject to overfishing in 2019. The retrospective analysis provided some confidence on the robustness of the model with respect to recent data. However, the catches in the last two years have exceeded the catch limit set for 2018 – 2000 and are also higher than the estimated target yield (Yield40%SSB). The estimated stock status is summarized as below:
• Catch in 2019:
547 248
• Average catch 2015–2019:
506 554
• Yield40%SSB (1000 t) (80% CI):
515 (445 –586)
• F40%SSB
0.60 (0.53–0.66)
• SB0(1000 t) (80% CI):
1900 (1614–2191)
• SB2019 (1000 t) (80% CI):
854 (632–1077)
• SB40%SB0
759 (641–877)
• SB2019 / SB40%SB0
1.13 (0.98–1.28)
• F2019 / F40%SB0
0.98 (0.75–1.21)
