方磊, 花传祥, 朱清澄. 基于体长世代分析法的秋刀鱼渔业资源评估研究[J]. 南方水产科学. DOI: 10.12131/20230237
引用本文: 方磊, 花传祥, 朱清澄. 基于体长世代分析法的秋刀鱼渔业资源评估研究[J]. 南方水产科学. DOI: 10.12131/20230237
FANG Lei, HUA Chuanxiang, ZHU Qingcheng. Study on fishery resource assessment of Pacific saury by Length-Based Cohort Analysis[J]. South China Fisheries Science. DOI: 10.12131/20230237
Citation: FANG Lei, HUA Chuanxiang, ZHU Qingcheng. Study on fishery resource assessment of Pacific saury by Length-Based Cohort Analysis[J]. South China Fisheries Science. DOI: 10.12131/20230237

基于体长世代分析法的秋刀鱼渔业资源评估研究

Study on fishery resource assessment of Pacific saury by Length-Based Cohort Analysis

  • 摘要: 秋刀鱼 (Cololabis saira) 分布于西北太平洋亚热带到温带水域,是中国远洋渔业主要的捕捞对象之一。为探究其资源状况,根据2014—2018年西北太平洋秋刀鱼的渔获体长组成和生物学数据,对体长世代分析 (Length-Based Cohort Analysis, LCA) 模型和基于生物量的体长世代分析 (Biomass-Based Length-Cohort Analysis, B-LCA) 模型进行性能检验和敏感性分析,并利用蒙特卡洛方法估算模型参数、秋刀鱼资源量、捕捞死亡系数以及最大持续产量。结果表明:1) 在5、10和15 mm体长间隔下,LCA模型和B-LCA模型均表现出优秀的拟合能力,且在5 mm体长间隔下,2种模型的拟合能力均更强;2) LCA模型对于以尾数为单位的渔业数据表现更佳,B-LCA模型对于以质量为单位的渔业数据表现更佳;3) LCA模型和B-LCA模型对bL的变化均较敏感,且对参数b的敏感程度更高;4) LCA模型估算的2014—2018年秋刀鱼平均资源质量约65.93×104~171.51×104 t,捕捞死亡系数为0.529 2,最大持续产量为37.73×104 t,而B-LCA模型估算的平均资源质量约47.88×104~126.25×104 t,捕捞死亡系数为0.540 5,最大持续产量为33.02×104 t。2种模型估算的最大持续产量均低于北太平洋渔业委员会 (North Pacific Ocean Commission, NPFC) 各成员国年均产量 (40.98×104 t),表明2014—2018年秋刀鱼资源处于过度捕捞状态。

     

    Abstract: Being one of the primary fishing targets in Chinese pelagic fishing, Pacific saury (Cololabis saira) is distributed in the subtropical to temperate waters of the northwest Pacific Ocean. In order to explore its resource status, according to the catch-at-size and biological data of Northwest Pacific saury from 2014 to 2018, we conducted performance tests and sensitivity analysis of Length-Based Cohort Analysis (LCA) model and Biomass-Based Length-Cohort Analysis (B-LCA) model. Besides, we applied Monte Carlo method to estimate the model parameters, resource quantity, fishing mortality coefficients and maximum sustainable yield of Pacific saury. The results show that: 1) The LCA model and B-LCA model exhibited excellent fitting abilities at 5, 10 and 15 mm length intervals, with stronger fitting abilities at 5 mm interval. 2) LCA model performed better for fishery data in units of number, while B-LCA model performed better for fishery data in units of mass. 3) Both LCA and B-LCA models were sensitive to changes in b and L_\infty , with higher sensitivity to parameter b. 4) The average resource mass of Pacific saury from 2014 to 2018 estimated by LCA model was about 65.93\times 10^4–171.51\times 10^4 t; the fishing mortality coefficient was 0.529 2; the maximum sustainable yield was 37.73\times 10^4 t. The average resource mass estimated by B-LCA model was about 47.88\times 10^4–126.25\times 10^4 t; the fishing mortality coefficient was 0.540 5; the maximum sustainable yield was 33.02\times 10^4 t. The maximum sustained production estimated by both models was lower than the average annual production of NPFC (North Pacific Ocean Commission) member countries ( 40.98\times 10^4 t), indicating that the Pacific saury resources had been overfished from 2014 to 2018.

     

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