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There is no best method for constructing size-transition matrices for size-structured stock assessments

机译:没有最佳的方法来构建用于尺寸结构的库存评估的尺寸转换矩阵

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摘要

Stock assessment methods for many invertebrate stocks, including crab stocks in the Bering Sea of Alaska, rely on size-structured population dynamics models. A key component of these models is the size-transition matrix, which specifies the probability of growing from one size-class to another after a certain period of time. Size-transition matrices can be defined using three parameters, the growth rate (k), asymptotic size (L-infinity), and variability in the size increment. Most assessments use mark-recapture data to estimate these parameters and assume that all individuals follow the same growth curve, but this can lead to biased estimates of growth parameters. We compared three approaches: the traditional approach, the platoon method, and a numerical integration method that allows k, L-infinity, or both to vary among individuals, under a variety of scenarios using simulated data based on golden king crabs (Lithodes aequispinus) in the Aleutian Islands region of Alaska. No estimation method performed best for all scenarios. The number of size-classes in the size-transition matrix and how the data are generated heavily dictate performance. However, we recommend the numerical integration method that allows L-infinity to vary among individuals and smaller size-class widths.
机译:许多无脊椎动物种群(包括阿拉斯加白令海螃蟹种群)的种群评估方法依赖于规模结构的种群动态模型。这些模型的关键组成部分是尺寸转换矩阵,该矩阵指定了在一定时间后从一种尺寸类别增长到另一种尺寸类别的可能性。大小转换矩阵可以使用三个参数定义,即增长率(k),渐近大小(L-无穷大)和大小增量的可变性。大多数评估使用标记夺回数据来估计这些参数,并假定所有个体都遵循相同的生长曲线,但这可能导致对生长参数的估计偏差。我们比较了三种方法:传统方法,排方法和数值积分方法,该方法允许使用基于金王蟹(Lithodes aequispinus)的模拟数据在各种情况下在个体之间改变k,L-无穷大或两者在个体之间变化。在阿拉斯加的阿留申群岛地区。没有一种估算方法在所有情况下都能达到最佳效果。尺寸转换矩阵中尺寸类别的数量以及如何生成数据在很大程度上决定了性能。但是,我们建议使用数值积分方法,该方法允许L无穷大在个体之间和较小的尺寸级宽度之间变化。

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