1. 上海海洋大学 海洋科学学院, 上海 201306;
2. 大洋渔业资源可持续开发省部共建教育部重点实验室, 上海 201306
官文江(1974-),副教授,研究方向为渔业资源评估.E-mail:wjguan@shou.edu.cn
S931
国家自然科学基金浙江两化融合联合基金（U1609202）；大洋渔业资源可持续开发省部共建教育部重点实验室开放基金项目（A1-0203-00-2009-2）.
1. College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;
2. The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China
多个模型被用于印度洋长鳍金枪鱼（）的资源评估，但这些模型的评估结果均存在较大的不确定性，为此，本文对影响印度洋长鳍金枪鱼资源评估的因素进行了分析。分析结果认为：（1）由于渔业数据存在不报、漏报或混报及采样样本数过低、采样协议出现变化等问题，造成印度洋长鳍金枪鱼渔业的渔获量、体长组成或年龄组成数据存在质量问题；（2）尽管对单位捕捞努力渔获量（catch per unit effort，CPUE）进行了标准化，但目标鱼种变化及捕捞努力量空间分布变化仍严重影响了标准化CPUE数据的质量；（3）印度洋长鳍金枪鱼的种群生态学及繁殖生物学研究仍比较薄弱，种群结构、繁殖、生长、自然死亡信息比较缺乏，在资源评估中，相关参数设置需借用其他洋区的研究结果；（4）海洋环境对印度洋长鳍金枪鱼的资源变动与空间分布具有显著影响，但评估模型较少考虑海洋环境的影响。由于上述问题的存在，导致当前评估结果存在较大不确定性。未来，应继续探索提高资源评估质量的方法，同时研究建立管理策略评价框架，以避免渔业资源评估结果的不确定性对该渔业可持续开发的影响。
The Indian Ocean albacore (), which is widely distributed in the Indian Ocean from 25°N to 40°S, is one of the main target species of the Indian Ocean commercial tuna fishery. In recent years, China longline fleets have also targeted the albacore in the Indian Ocean. At present, several stock assessment models have been used to assess the Indian Ocean albacore tuna to determine the status of their stocks. However, there has been a substantial uncertainty regarding the results of these models. Therefore, in this paper, we have analyzed the factors influencing stock assessment for the Indian Ocean albacore tuna. This paper argues that:(1) substantial uncertainty exists in the catch and catch-at-size or catch-at-age data, because there were no, or incomplete, or incorrectly classified data from some important fleets reported, and the number of samples for size frequency data was very low, or the sampling protocols of the collection of size data changed with time; (2) although the catch per unit effort (CPUE) was standardized, the impacts of the changes in target species and the inhomogeneous distribution of fishing efforts of the fleets have still degraded the quality of the standardized CPUE; (3) because there were very few or limited studies on the biology of the Indian Ocean albacore, knowledge about their population structure, reproduction, growth, and natural mortality is limited, which has led to the values of some important biological parameters in the stock assessment models being set by using the results from the other oceans; (4) although the ocean environment has significant influences on the biomass dynamics and distribution of the Indian ocean albacore, only a few stock assessment models take these influences into account. These aforementioned issues have resulted in great uncertainties of the stock assessment. In the future, we need to further explore approaches to improve the quality of the stock assessment. However, at the same time, we have to develop a management strategy evaluation framework for the Indian Ocean albacore tuna to avoid the impacts of uncertainties of the stock assessment on the sustainable development of the fishery.
官文江,朱江峰,高峰.印度洋长鳍金枪鱼资源评估的影响因素分析[J].中国水产科学,2018,25(5):1102-1114
GUAN Wenjiang, ZHU Jiangfeng, GAO Feng. Analysis of influencing factors on stock assessment of the Indian Ocean albacore tuna (Thunnus alalunga)[J]. Journal of Fishery Sciences of China,2018,25(5):1102-1114
