In temperate waters, growth and mortality of bony fishes are frequently estimated from age information derived from the examination of annular rings on hard structures (e.g., otoliths). However, determining ages from hard structures can be time consuming, often requires sacrificing fish, and has associated costs for supplies and personnel time in processing or reading structures. Subsampling based on a target number of fish per length bin is commonly used to reduce time and costs but may introduce biases into the estimation of population characteristics. We wanted to understand how interactive effects of bin width, gear selectivity, and length‐at‐age variability influence the estimation of growth parameters, total instantaneous mortality (Z), and age frequency. We developed a simulation model to generate populations under the assumption that growth followed the von Bertalanffy growth model; we then sampled from those populations for age analysis based on no gear selectivity, dome‐shaped selectivity, and logistic selectivity. Furthermore, we wanted to determine whether observed biases could be corrected by using a weighting procedure during growth model fitting. Fifteen subsampling schemes were evaluated, with five different length bin widths and three target subsample sizes for each bin (subsampling levels). Gear selectivity, variability in length at age, and estimation procedures had a greater and more predictable influence on growth parameters than bin widths for size‐based subsampling. Dome‐shaped gear selectivity was associated with biases in growth parameter and Z estimation. Weighted regression based on weighting factors calculated from the original sample's length frequency generally improved the consistency of growth parameter estimates among subsampling schemes but did not always improve accuracy. No bin widths or subsample sizes were clearly superior across modeled scenarios. Consequently, alteration of bin widths seems less useful in reducing biases than using alternative estimation methods for population characteristics of interest and considering other external factors.

中文翻译：

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基于大小的年龄二次抽样中与变化的bin数相关的人口特征估计中偏差估计的模拟研究

在温带水域中，经常根据对硬质结构（例如耳石）上的环形环的检查得出的年龄信息来估算骨鱼的生长和死亡率。但是，从坚硬的结构中确定年龄可能很耗时，常常需要牺牲鱼类，并且在处理或读取结构时会产生相关的物资成本和人员时间。通常使用基于每个长度箱的目标鱼类数量的二次采样来减少时间和成本，但可能会在种群特征的估计中引入偏差。我们想了解垃圾箱宽度，齿轮选择性和年龄长度可变性的交互作用如何影响生长参数，总瞬时死亡率（Z）和年龄频率。我们假设增长遵循von Bertalanffy增长模型，因此开发了一个模拟模型来生成种群。然后，我们从这些人群中进行抽样，以基于无齿轮选择性，圆顶形选择性和逻辑对数选择性进行年龄分析。此外，我们想确定在增长模型拟合过程中是否可以通过使用加权程序来校正观察到的偏差。评估了15种子采样方案，每个子仓具有5种不同长度的条带宽度和3种目标子采样大小（子采样级别）。与基于大小的子采样的箱宽相比，齿轮的选择性，年龄长度的可变性以及估算程序对生长参数的影响更大，更可预测。圆顶形齿轮的选择性与生长参数的偏差和Z估计。基于从原始样本的长度频率计算得出的加权因子的加权回归通常可以提高子采样方案中生长参数估计值的一致性，但并不总能提高准确性。在模拟的场景中，没有bin宽度或子样本大小明显优越。因此，与使用替代估计方法来关注目标人口特征并考虑其他外部因素相比，改变条带宽度似乎在减少偏差方面没有多大用处。