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Close-kin methods to estimate census size and effective population size
Fish and Fisheries ( IF 5.6 ) Pub Date : 2021-10-20 , DOI: 10.1111/faf.12615
Robin S. Waples 1 , Pierre Feutry 2
Affiliation  

The last two decades have witnessed rapid developments and increasing interest in use of: (1) genetic methods to estimate effective population size (Ne) and (2) close-kin mark–recapture (CKMR) methods to estimate abundance based on the incidence of close relatives. Whereas Ne estimation methods have been applied to a wide range of taxa, all CKMR applications to date have been for aquatic species. These two fields of inquiry have developed largely independently, and this is unfortunate because deeper insights can be gained by joint evaluation of eco-evolutionary processes. In this synthesis, we use simple analytical models and simulated pedigree data to illustrate how various factors (life-history traits; patterns of variation in individual reproductive success; experimental design; stochasticity; marker type) can affect the performance of the estimators. We show that the Ne/N ratio and the probability of a close-kin match both depend on a vector of parental weights that specify relative probabilities that different individuals will produce offspring. Although age-specific vital rates are central to both methodologies, for CKMR they can potentially bias abundance estimates unless properly accounted for, whereas they represent the signals of genetic drift that Ne estimation methods depend upon. Coordinating Ne and CKMR estimation methods using the same or overlapping datasets would facilitate joint evaluation of both the ecological and evolutionary consequences of abundance.

中文翻译:

估计人口普查规模和有效人口规模的近亲方法

过去 20 年见证了快速发展和越来越多的使用兴趣:(1) 估计有效种群大小 ( N e ) 的遗传方法和 (2) 近亲标记-重新捕获 (CKMR) 方法根据发病率估计丰度的近亲。而N e估计方法已应用于广泛的分类群,迄今为止所有 CKMR 应用都针对水生物种。这两个研究领域在很大程度上是独立发展的,这是不幸的,因为通过对生态进化过程的联合评估可以获得更深入的见解。在这个综合中,我们使用简单的分析模型和模拟谱系数据来说明各种因素(生活史特征;个体繁殖成功的变异模式;实验设计;随机性;标记类型)如何影响估计器的性能。我们证明了N e / N比率和近亲匹配的概率都取决于父母权重的向量,该向量指定了不同个体将产生后代的相对概率。尽管特定年龄的生命率是这两种方法的核心,但对于 CKMR,除非适当考虑,否则它们可能会使丰度估计产生偏差,而它们代表了N e估计方法所依赖的遗传漂移信号。使用相同或重叠的数据集协调N e和 CKMR 估计方法将有助于联合评估丰度的生态和进化后果。
更新日期:2021-10-20
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