数据不确定性对西北太平洋两种混栖鲐生长研究的影响OA北大核心CSTPCD
Impact of data uncertainties on growth of two coexisting mackerel species in Northwest Pacific Ocean
依据2020-2023年"淞航"号渔业资源科学调查与生产船围网的鲐调查数据,着重分析了种类鉴定不确定性和不同数据来源(是否基于渔业生产获取的数据)对日本鲐和澳洲鲐生长特征的影响.研究发现,生产船样本肥满度略小于"淞航"号,且"淞航"号样本体质量增长更快,摄食情况相对较好.叉长-体质量关系的拟合结果表明,相同叉长下,澳洲鲐体质量小于日本鲐;不同数据来源与不同物种所求a值范围为1.886×10-6~6.721×10-5,b值多数大于3.a值变化较大,说明西北太平洋2021-2023年际水域环境变化较大;除2020年生产船日本鲐b值较小(b=2.66),为负异速增长外,其余均为正异速增长.依据混合效应模型对样本的叉长-体质量关系进行异质性分析,结果表明数据来源与年份对日本鲐与澳洲鲐生长研究结果的影响更显著,物种间差异不显著.在基于生长等生活史特征的相关鱼种资源评估和管理的过程中,建议充分考虑时间差异和不同数据来源导致的不确定性,而不是采用恒定的、缺乏时间变化和数据来源考虑的生活史参数;此外,鉴于实际操作的可行性和成本,暂时可不区分日本鲐和澳洲鲐,但仍然建议在科学研究过程中进一步探讨可能的影响.
This study used the Chub mackerel Scomber japonicus and Blue mackerel S.australasicus samples derived from both scientific survey and fishing vessels between 2020 and 2023,and analyzed the influence of species identification,different data sources and time variations on individual growth.The results revealed that the fattiness of samples from fishing vessels was slightly lower than that of scientific survey,and the body mass of samples from scientific survey grew faster.The length-body mass relationship showed that under the same fork length,the body mass of Blue mackerel was lighter than that of Chub mackerel.The range of condition factor was 1.886×10-6-6.721×10-5,with the exponent coefficient b mostly greater than 3.Heterogeneity analysis indicated that there were significant influence of data sources and years on the mackerels'growth,without significant growth difference between Chub mackerel and Blue mackerel in Northwest Pacific Ocean.Therefore,time-varying growth parameters and their uncertainties from different data sources of mackerels are strongly suggested to be considered during the stock assessment and fishery management which require life history traits.Additionally,species distinguishment between two mackerels could be given lower priority during data collection and management,but still deserve concern in the future research.
刘芷维;周雨霏;郑琳琳;麻秋云;崔明远
上海海洋大学海洋生物资源与管理学院,上海 201306上海海洋大学海洋生物资源与管理学院,上海 201306||国家远洋渔业工程技术研究中心,上海 201306||大洋渔业资源可持续开发教育部重点实验室,上海 201306
水产学
西北太平洋鲐生长特征数据不确定性混合效应模型
Northwest Pacific Oceanuncertaintiesmackerelgrowthlinear mixed-effects model
《上海海洋大学学报》 2024 (004)
848-858 / 11
国家自然科学基金(32202934);农业农村部全球渔业资源调查监测评估(公海渔业资源综合科学调查)专项(D-8025-23-1002);上海市高校特聘教授"东方学者"岗位跟踪计划(GZ2022011)
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