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Modelling stochastic fish stock dynamics using Markov Chain Monte Carlo

机译:使用马尔可夫链蒙特卡洛模拟随机鱼类种群动态

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摘要

A new age-structured stock dynamics approach including stochastic survival and recruitment processes is developed and implemented. The model is able to analyse detailed sources of information used in standard age-based fish stock assessment such as catch-at-age and effort data from commercial fleets and research surveys. The stock numbers are treated as unobserved variables subject to process errors while the catches are observed variables subject to both sampling and process errors. Results obtained for North Sea plaice using Markov Chain Monte Carlo methods indicate that the process error by far accounts for most of the variation compared to sampling error. Comparison with results from a simpler separable model indicates that the new model provides more precise estimates with fewer parameters.
机译:开发并实施了一种新的具有年龄结构的股票动态方法,包括随机生存和募集过程。该模型能够分析基于标准年龄的鱼类种群评估中使用的详细信息源,例如商业船队的捕捞量和工作量数据以及研究调查。存货数量被视为不受制程误差的变量,而渔获量则是受制于抽样误差和制程误差的变量。使用马尔可夫链蒙特卡罗方法获得的北海的结果表明,与采样误差相比,到目前为止,过程误差占了大部分变化。与来自更简单的可分离模型的结果的比较表明,新模型使用更少的参数提供了更精确的估计。

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