| 海洋环境因子对澳洲鲐亲体补充量关系的影响——基于贝叶斯模型平均法的研究 |
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| 引用本文： | 张畅,陈新军.海洋环境因子对澳洲鲐亲体补充量关系的影响——基于贝叶斯模型平均法的研究[J].海洋学报,2019,41(2):99-106. |
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| 作者姓名： | 张畅 陈新军 |
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| 作者单位： | 上海海洋大学 海洋科学学院,上海,201306;上海海洋大学 海洋科学学院,上海 201306;青岛海洋科学与技术试点国家实验室 海洋渔业科学与食物产出过程功能实验室,山东 青岛 266071;大洋渔业资源可持续开发教育部重点实验室,上海 201306;上海海洋大学 国家远洋渔业工程技术研究中心,上海 201306;农业农村部大洋渔业开发重点实验室,上海 201306 |
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| 基金项目： | 海洋局公益性行业专项（20155014）；上海市科技创新计划（15DZ1202200）。 |
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| 摘 要： | 澳洲鲐（Scomber australasicus）是西北太平洋重要的中上层经济鱼类，生命周期相对较短，资源量受补充量影响明显，了解澳洲鲐太平洋群系补充量状况对掌握其资源量及确保其可持续利用具有重要的意义。本文利用产卵场1（30°~32°N，130°~132°E）海表面温度（sea surface temperature，SST1）、产卵场2（34°~35°N，138°~141°E）海表面温度（SST2）、索饵场（35°~45°N，140°~160°E）海表面温度（SST3）、潮位差（tidal range，TR）、太平洋年代际涛动（Pacific decadal oscillation，PDO）和亲体量（spawning stock biomass，SSB）6个影响因子任意组合与补充量构建多个模型，运用贝叶斯模型平均法（Bayesian model averaging，BMA）分析各个环境因子对资源补充量的解释能力，并预测其补充量的变化。结果表明，SSB对补充量具有最长期且稳定的解释能力，其次是SST3，PDO、TR、SST2、SST1也对补充量模型具有一定的解释能力。SST3是环境因子中影响最大的因子，可能是由于补充群体在索饵场内生活时间较长，索饵场温度对仔鱼或鱼卵的生长存活有较大的影响。研究认为，基于BMA的组合预报综合考虑了各个模型的优势，优于单一模型，可用于澳洲鲐资源补充量的预测。
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| 关 键 词： | 澳洲鲐 太平洋群系 贝叶斯模型平均法 索饵场 产卵场 |
| 收稿时间： | 2018/1/21 0:00:00 |
| 修稿时间： | 2018/5/17 0:00:00 |
The impact of environmental factors on stock-recruitment relationship of spotted mackerel-based on Bayesian model averaging method |
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| Zhang Chang and Chen Xinjun.The impact of environmental factors on stock-recruitment relationship of spotted mackerel-based on Bayesian model averaging method[J].Acta Oceanologica Sinica (in Chinese),2019,41(2):99-106. |
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| Authors: | Zhang Chang and Chen Xinjun |
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| Institution: | College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China and College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology(Qingdao), Qingdao 266237, China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China;National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Ocean Fisheries Exploitation, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China |
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| Abstract: | Spotted mackerel (Scomber australasicus) is an important pelagic and economic species in northwest Pacific. The life cycle is relatively short, and the stock resources is obviously affected by the recruitment. It is important to know the recruitment of spotted mackerel for the stock resources and sustainable utilization. The data include 6 factors which are sea surface temperature of first spawning ground (SST1), sea surface temperature of second spawning ground(SST2), sea surface temperature of feeding ground (SST3), tidal range (TR), Pacific decadal oscillation(PDO) and spawning stock biomass(SSB), all factors and recruitment are used to build the forecasting model. The Bayesian model averaging (BMA) not only give us the importance of the factors in explaining the recruitment, but also can predict the recruitment. The result shows the spawning stock biomass is most important factor for recruitment with long and stable explanatory ability, the second is SST3, which may be due to the fact that supplemental groups lived longer in the feeding grounds and the temperature of the feeding grounds had a greater impact on the growth and survival of larvae or eggs. Meanwhile, PDO, TR, SST2 and SST1 are also important for recruitment models. The forecast, based on BMA which takes the advantages of each model into consideration, is better than single models, and can be used for the recruitment prediction of spotted mackerel. |
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| Keywords: | Scomber australasicus the Pacific stock Bayesian model averaging feeding ground spawning ground |
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