Building genetic networks using relatedness information: a novel approach for the estimation of dispersal and characterization of group structure in social animals
Building genetic networks using relatedness information: a novel approach for the estimation of dispersal and characterization of group structure in social animals
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使用相关性信息构建遗传网络：一种估计社会动物群体结构扩散和表征的新方法
DOI：
10.1111/j.1365-294x.2012.05492.x
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发表时间：
2012
影响因子：
4.9
通讯作者：
S. Griffith
中科院分区：
文献类型：
--
作者：
L. Rollins;L. E. Browning;C. Holleley;James L. Savage;A. Russell;S. Griffith
因此，正确理解分散行为的潜在因素对种群动力学、行为生态学和保护生物学等许多领域都至关重要。然而，尽管使用直接和间接方法进行了多年的研究，个体的扩散模式仍然难以量化。在本研究中，我们利用两两亲缘关系数据和社会网络方法组合而成的遗传网络，对合作繁殖的栗冠鹦鹉（Pomatostomus ruficeps）的单个深入研究种群的扩散进行了量化，并将其与来自观察数据的扩散估计进行了比较。这种新颖的方法不仅确定了我们研究地点内社会群体之间的运动，而且还提供了来自研究地点以外的个人移民率的估计。遗传数据和重新观测数据都表明，雌鱼的扩散倾向明显，但遗传数据估计的扩散幅度要大得多。这表明许多以前的研究依赖于标记再捕获数据可能大大低估了分散。对样本种群内空间遗传结构的分析也支持了雌性更具分散性的观点，雌性在自己的社会群体范围之外没有任何结构，而雄性的遗传结构则从其社会群体向外扩展750米。虽然我们使用的遗传网络方法是可视化社会动物和遗传微观结构以及识别分散者的优秀工具，但我们的结果也表明将它们与行为和生活史数据并行应用的重要性。
Natal dispersal is an important life history trait driving variation in individual fitness, and therefore, a proper understanding of the factors underlying dispersal behaviour is critical to many fields including population dynamics, behavioural ecology and conservation biology. However, individual dispersal patterns remain difficult to quantify despite many years of research using direct and indirect methods. Here, we quantify dispersal in a single intensively studied population of the cooperatively breeding chestnut‐crowned babbler (Pomatostomus ruficeps) using genetic networks created from the combination of pairwise relatedness data and social networking methods and compare this to dispersal estimates from re‐sighting data. This novel approach not only identifies movements between social groups within our study sites but also provides an estimation of immigration rates of individuals originating outside the study site. Both genetic and re‐sighting data indicated that dispersal was strongly female biased, but the magnitude of dispersal estimates was much greater using genetic data. This suggests that many previous studies relying on mark–recapture data may have significantly underestimated dispersal. An analysis of spatial genetic structure within the sampled population also supports the idea that females are more dispersive, with females having no structure beyond the bounds of their own social group, while male genetic structure expands for 750 m from their social group. Although the genetic network approach we have used is an excellent tool for visualizing the social and genetic microstructure of social animals and identifying dispersers, our results also indicate the importance of applying them in parallel with behavioural and life history data.
影响因子：
3.3
作者：
M. Lynch;K. Ritland
通讯作者：
M. Lynch;K. Ritland
影响因子：
--
作者：
Ranajit Chakraborty;Li Jin
通讯作者：
Ranajit Chakraborty;Li Jin
影响因子：
3.3
作者：
G. Wilson;B. Rannala
通讯作者：
G. Wilson;B. Rannala