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Modelling the dynamics of the deepwater shark Centroscymnus coelolepis off mainland Portugal

机译:对葡萄牙大陆附近深水鲨Centroscymnus coelolepis的动力学建模

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A statistical approach to evaluate the temporal trends in the abundance of female Centroscymnus coelolepis in Portuguese waters of ICES division IXa is presented. A state space model is used, which integrates all the available information of the species' life history as well as knowledge of its biological dynamics. The model involves two processes that run in parallel: a non-observed process (the state process) that describes the annual female population abundance and an observational process of annual fisheries catches in numbers, assumed to be measured with error. Estimation is done within the Bayesian paradigm using sequential importance sampling with resampling. To evaluate the sensitivity of the model to the prior distributions chosen for theparameters, three scenarios with different levels of prior information were considered. Trends in population abundance level and the abundance levels themselves are quite similar in the two scenarios using biological information, but the model that incorporated all the available biological information in the priors provided the best fit to the observed data. The results indicate that taking into account the main biological drivers and the fishing information in the same state space model provides a coherent picture of the population abundance trends, further suggesting that the fishing impact on the population inhabiting Portuguese mainland waters was low.
机译:提出了一种统计方法,用于评估ICES IXa分区葡萄牙水域中的腔肠鱼类Celolecycymnus coelolepis数量的时间趋势。使用状态空间模型,该模型整合了该物种生活史的所有可用信息以及其生物动力学知识。该模型涉及两个并行运行的过程:一个非观察性过程(状态过程),该过程描述了年度女性种群的数量;以及一个观测的年度渔业捕捞数量的观察过程,假定该过程有误差。估计是在贝叶斯范式中使用具有重采样的顺序重要性采样进行的。为了评估模型对为参数选择的先验分布的敏感性,考虑了具有不同先验信息水平的三种情况。在使用生物信息的两种情况下,人口丰度水平的趋势及其本身的丰度水平非常相似,但是先验中包含所有可用生物信息的模型最适合观察到的数据。结果表明,在同一状态空间模型中考虑主要的生物驱动因素和捕捞信息,可以提供有关人口数量趋势的连贯图景,进一步表明,捕捞对居住在葡萄牙内陆水域的人口的影响很小。

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