Determining the origin of individuals in mixed population samples is key in many ecological, conservation and management contexts. Genetic data can be analyzed using genetic stock identification (GSI), where the origin of single individuals is determined using Individual Assignment (IA) and population proportions are estimated with Mixed Stock Analysis (MSA). In such analyses, allele frequencies in a reference baseline are required. Unknown individuals or mixture proportions are assigned to source populations based on the likelihood that their multilocus genotypes occur in a particular baseline sample. Representative sampling of populations included in a baseline is important when designing and performing GSI. Here, we investigate the effects of family sampling on GSI, using both simulated and empirical genotypes for Atlantic salmon (Salmo salar). We show that nonrepresentative sampling leading to inclusion of close relatives in a reference baseline may introduce bias in estimated proportions of contributing populations in a mixed sample, and increases the amount of incorrectly assigned individual fish. Simulated data further show that the induced bias increases with increasing family structure, but that it can be partly mitigated by increased baseline population sample sizes. Results from standard accuracy tests of GSI (using only a reference baseline and/or self-assignment) gave a false and elevated indication of the baseline power and accuracy to identify stock proportions and individuals. These findings suggest that family structure in baseline population samples should be quantified and its consequences evaluated, before carrying out GSI.

中文翻译：

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人口样本中的近亲：遗传种群鉴定的后果评估。

在许多生态，保护和管理环境中，确定混合种群样本中个体的来源很关键。可以使用遗传种群识别（GSI）来分析遗传数据，其中单个个体的起源通过“个体分配”（IA）确定，而种群比例则通过“混合种群分析”（MSA）进行估算。在此类分析中，需要参考基线中的等位基因频率。根据未知人群或混合比例，将其多基因座基因型出现在特定基线样本中的可能性分配给源人群。在设计和执行GSI时，对基线中包含的总体样本进行代表性采样很重要。在这里，我们使用大西洋鲑鱼（Salmo salar）的模拟和经验基因型研究家庭抽样对GSI的影响。我们表明，导致代表性近亲纳入参考基线的非代表性采样可能会导致混合样本中贡献种群的估计比例出现偏差，并增加了错误分配的个体鱼的数量。模拟数据进一步表明，诱导的偏见随家庭结构的增加而增加，但是可以通过增加基线人群样本量来部分缓解。GSI标准准确性测试的结果（仅使用参考基线和/或自我分配）对基线能力和准确性进行了虚假和高估，以识别存货比例和个体。这些发现表明，在进行GSI之前，应该对基线人群样本中的家庭结构进行量化并评估其后果。