首页> 外文期刊>ICES Journal of Marine Science >Hierarchical model-based estimation of population growth curves for redfish (Sebastes mentella and Sebastes fasciatus) off the Eastern coast of Canada
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Hierarchical model-based estimation of population growth curves for redfish (Sebastes mentella and Sebastes fasciatus) off the Eastern coast of Canada

机译:基于分层模型的加拿大东部沿海红鱼(塞巴斯蒂斯门特拉鱼和塞巴斯蒂斯fasciatus)种群增长曲线的估计

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摘要

Northwest Atlantic (NWA) redfish (Sebastes mentella and Sebastes fasciatus) stocks are currently assessed using survey indicators and age-aggregated production models rather than age-based models because routine age readings are not available due to the difficulty in obtaining reliable measurements for these fish. However, recruitment is highly variable for redfish species so age-aggregated production models are not a good approach to provide short-term harvest advice. Recently a relatively large dataset of validated age readings was published that provide a good basis to model growth and its variability [i.e. population growth curve (PGC)]. In this article we propose a hierarchical random effects growth model that includes between-individual variation to estimate PGCs for 10 NWA redfish stocks and for males and females separately. These growth curves are required to develop age-based stock assessment models. External estimates of measurement error in length and age are included in our model to separate these sources of variation from the PGC variability. The hierarchical approach leads to more realistic growth curves than if each stock and sex are modelled separately. Model results indicated that S. mentella usually grow to larger sizes than S. fasciatus and that females of both these species grow to larger sizes than males. There was little evidence of a change in growth rates over time.
机译:目前,西北大西洋(NWA)红鱼(Sebastes mentella和Sebastes fasciatus)的种群是使用调查指标和年龄汇总的生产模型而不是基于年龄的模型进行评估的,因为无法获得常规的年龄读数,因为难以获得这些鱼的可靠测量结果。但是,红鱼物种的招募变化很大,因此年龄综合生产模型不是提供短期收获建议的好方法。最近,发布了一个相对较大的经过验证的年龄数据集,该数据集为模型生长及其变异性提供了良好的基础[即人口增长曲线(PGC)]。在本文中,我们提出了一个分层的随机效应增长模型,该模型包括个体间的差异,以估计10种NWA红鱼种群以及雄性和雌性的PGC。这些增长曲线是开发基于年龄的股票评估模型所必需的。我们在模型中包括长度和年龄的测量误差的外部估计,以将这些变异源与PGC变异性分开。与单独对每种股票和性别进行建模相比,采用分层方法可以得出更现实的增长曲线。模型结果表明,门氏链球菌通常长到筋膜长杆菌,而这两个物种的雌性长于男性。几乎没有证据表明增长率会随时间变化。

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