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Ridge virtual population analysis to reduce the instability of fishing mortalities in the terminal year

机译:岭虚拟种群分析,以减少最终年份捕捞死亡率的不稳定

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摘要

Tuned virtual population analyses are widely used for fisheries stock assessments. However, accurately estimating abundances and fishing mortality coefficients in the terminal year using tuned virtual population analyses is generally difficult, particularly when there is a limited number of available abundance indices. We propose a new method of integrating the tuned virtual population analyses with a ridge regression approach. In our method, penalization in the ridge regression is applied to the age-specific fishing mortalities in the terminal year, and the penalty parameter is automatically selected by minimizing the retrospective bias. Therefore, our method is able to simultaneously obtain a stable estimation of fishing mortality coefficients in the terminal year and reduce retrospective bias. Simulation tests based on the northern Japan Sea stock of walleye pollock (Gadus chalcogrammus) in the Sea of Japan demonstrated that this method yielded less biased estimates of abundances and avoided overestimations of fishing mortality coefficients in the terminal year. In addition, despite limited abundance indices, our method can perform reliable abundance estimations even under hyperstability and hyperdepletion conditions.
机译:调整后的虚拟种群分析被广泛用于渔业种群评估。但是,使用已调整的虚拟种群分析来准确估计末年的丰度和捕鱼死亡率系数通常很困难,尤其是在可用丰度指数有限的情况下。我们提出了一种新的方法,将调整后的虚拟总体分析与岭回归方法相集成。在我们的方法中,将岭回归中的惩罚应用于末年特定年龄的捕捞死亡率,并通过最小化追溯偏差来自动选择惩罚参数。因此,我们的方法能够同时获得末年捕捞死亡率系数的稳定估计,并减少追溯偏差。基于日本北部日本海在日本海中的角膜白头((Gadus chalcogrammus)种群的模拟测试表明,这种方法产生的丰度估计值偏少,并且避免了在最后一年高估捕鱼死亡率系数。此外,尽管丰度指数有限,我们的方法即使在超稳定性和超耗尽条件下也可以执行可靠的丰度估计。

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