Stock assessment for albacore tuna (Thunnus alalunga) in the Indian Ocean based on JABBA-Select model under different time series of catch and fishing vessel effects
YANG Shiyu，FENG Ji，ZHU Jiangfeng*
1.College of Marine Sciences，Shanghai Ocean University，Shanghai 201306，China；2.Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources，Ministry of Education，Shanghai 201306，China；3.Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources，Ministry of Agriculture and Rural Affairs，Shanghai 201306，China
Abstract: In order to understand population dynamics and resource exploitation status of albacore tuna (Thunnusalalunga) in the Indian Ocean and to promote the sustainable exploitation of the fishery resources, the JABBA-Select model combining the biological parameters of the stock and fishery selectivity was used to assess albacore tuna, focusing on the impact of different time series of catch and with or without considering the fishing vessel effects in standardized CPUE on the stock assessment. The results showed that the model with short time series of catch from 1979 to 2020 and longline CPUE with vessel effect fitted better than the model with time series from 1950 to 2020, resulting in the estimated stock neither to be overfished (BSB/BSB,MSY>1) nor subject to overfishing (F/FMSY<1) in 2020. The sensitivity analysis indicated that the stock assessment results were robust to steepness (h), but sensitive to natural mortality (M). The finding showed that the stock assessment results varied with different time series of catch data, and the standardized CPUE considering the fishing vessel effect better reflected the dynamics of stock,with decrease in the uncertainty of assessment.
杨诗玉, 冯佶, 朱江峰. 基于JABBA-Select模型对不同时间序列渔获量和渔船效应的印度洋长鳍金枪鱼资源评估[J]. 大连海洋大学学报, 2023, 38(5): 828-838.
YANG Shiyu, FENG Ji, ZHU Jiangfeng. Stock assessment for albacore tuna (Thunnus alalunga) in the Indian Ocean based on JABBA-Select model under different time series of catch and fishing vessel effects. Journal of Dalian Ocean University, 2023, 38(5): 828-838.
2023, Vol. 38 
