单 位：
上海海洋大学海洋科学学院;大洋生物资源开发和利用上海市高校重点实验室;大洋渔业资源可持续开发省部共建教育部重点实验室
关键词：
长鳍金枪鱼;东太平洋;个体大小;钓获深度
摘 要：
长鳍金枪鱼(Thunnus alalunga)具有重要的经济价值,其个体大小与钓获深度有一定的关联。本研究利用2013年东太平洋渔业观察员的数据,将渔获物分为76~85 cm、86~95 cm、96~105 cm、106~115 cm和116~125 cm 5个叉长组,运用悬链线公式得到钓获深度,统计各叉长组渔获个体钩位差异和各钩位渔获个体大小差异,分析个体大小与钓获深度的关系,得到结果如下:渔获物钓获深度范围为61.3~236.1 m。各叉长组主要渔获钩位随叉长增大而增大。各钩位主要渔获个体随序号增大而增大。76~85 cm叉长组的渔获物主要分布在61.3~121.8 m水层,平均钓获深度为(110.6±11.7)m;86~95 cm叉长组的在102.3~174.4 m,平均钓获深度为(144.1±4.5)m;96~105 cm叉长组的在189.4~202.8 m,平均钓获深度为(184.9±1.6)m;106~115 cm叉长组的在214.3~223.6 m,平均钓获深度为(193.8±3.8)m;116~125 cm叉长组的在230.5~236.1 m,平均钓获深度为(219.3±7.2)m。研究结果表明:东太平洋长鳍金枪鱼随叉长增大,栖息深度也加深,二者有相关关系。生产时调整钓具深度可有效保护资源可持续发展。
译 名：
Preliminary research on size difference and depth environment of Thunnus alalunga in East Pacific
作 者：
ZHAI Tian-chen;DAI Xiao-jie;ZHU Jiang-feng;College of Marine Sciences,Shanghai Ocean University;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources,Ministry of Education;Key Laboratory of Shanghai Education Commission for Oceanic Fisheries Resources Exploitation;
关键词：
albacore;;East Pacific;;fork length;;depth
摘 要：
Thunnus alalunga,an important branch of tunas,has great economic values. Studies on albacore tuna are thorough,especially on resources status,biology and reproductive biology. However,the relationship between body size and living depth of the fish has been rarely studied in China. Since learning this relationship will have a significant impact on both commercial fishing and resource sustainable development,the author went to East Pacific and worked as a fishery observer for 7 months to gather data. This study used the data from October to December in 2013 to trace the relevance. The operating range was from 13° 58' to21° 55' S,and from 120° 54' to 135° 32' W,which was to the east of French Polynesia. There were 87 sets altogether in this area. The data contained fork length of albacore,set locations and fishing gear information like length of float line,length of branch line,main line length between branch lines and so on. The data of fishing gear was used to calculate caught depth by catenary equation. The author divided the catch into five groups by fork length: 76-85 cm,86-95 cm,86-95 cm,106-115 cm and 116-125 cm. The paper used catenary equation to calculate theoretical caught depth,and assumed the relative shoaling was 20% to calculate modified depth. Statistics percentages among hooks in each fork length group was calculated to find out the favorite depth of each group. Statistics average fork length in each hook was calculated to find out the most common size of each hook. Considering both above,the author analyzed the relationship between size difference and depth environment and the results were as follows: the catching depth range was 61. 3-236. 1m. In each fork length group,with the fork length getting longer,the average depth was deeper. And as the hook getting deeper,the fork length became longer. 76-85 cm fork length group was mainly distributed in61. 3-121. 8 m,with an average depth of( 110. 6 ± 11. 7) m; 86-95 cm in 102. 3-174. 4 m,with an average depth of( 144. 1 ± 4. 5) m; 96-105 cm in 189. 4-202. 8 m with an average depth of( 184. 9 ± 1.6) m; 106-115 cm in 214. 3-223. 6 m with an average depth of( 193. 8 ± 3. 8) m; 116-125 cm in 230. 5-236. 1 m with an average depth of( 219. 3 ± 7. 2) m. Those results showed that the albacores in eastern Pacific had deeper perching depth when they got larger. There was a clear relationship between them,and if we adjust the fishing gear depth it can effectively protect resources and sustainable development. However,because the author was working with a commercial fishing vessel,data collection was limited. The relative shoaling was hypothetical,and the modified depth had deviation. Also,to record each fish's caught time was not practical and tunas had a vertical distribution between day and night,the results would have deviation from this too. For now,deviations can't be avoided. The direction of future research is to use electric tag on a certain amount of albacore to get the depth data in time.
