Cardilini Adam P A, Sherman Craig D H, Sherwin William B, Rollins Lee A
Faculty of Science, Engineering and Built Envrionment, Deakin University, Waurn Ponds, Vic, Australia.
Centre for Integrative Ecology, Deakin University, Waurn Ponds, Vic, Australia.
PeerJ. 2018 Mar 29;6:e4573. doi: 10.7717/peerj.4573. eCollection 2018.
Empirical genetic datasets used for estimating contemporary dispersal in wild populations and to correctly identify dispersers are rarely tested to determine if they are capable of providing accurate results. Here we test whether a genetic dataset provides sufficient information to accurately identify first-generation dispersers. Using microsatellite data from three wild populations of common starlings (), we artificially simulated dispersal of a subset of individuals; we term this 'Simulated Disperser Analysis'. We then ran analyses for diminishing numbers of loci, to assess at which point simulated dispersers could no longer be correctly identified. Not surprisingly, the correct identification of dispersers varied significantly depending on the individual chosen to 'disperse', the number of loci used, whether loci had high or low Polymorphic Information Content and the location to which the dispersers were moved. A review of the literature revealed that studies that have implemented first-generation migrant detection to date have used on average 10 microsatellite loci. Our results suggest at least 27 loci are required to accurately identify dispersers in the study system evaluated here. We suggest that future studies use the approach we describe to determine the appropriate number of markers needed to accurately identify dispersers in their study system; the unique nature of natural systems means that the number of markers required for each study system will vary. Future studies can use Simulated Disperser Analysis on pilot data to test marker panels for robustness to contemporary dispersal identification, providing a powerful tool in the efficient and accurate design of studies using genetic data to estimate dispersal.
用于估计野生种群当代扩散情况并正确识别扩散个体的经验性遗传数据集，很少经过测试以确定它们是否能够提供准确的结果。在此，我们测试一个遗传数据集是否能提供足够的信息来准确识别第一代扩散个体。利用来自三个家八哥野生种群的微卫星数据，我们人工模拟了一部分个体的扩散；我们将此称为“模拟扩散个体分析”。然后，我们针对逐渐减少的基因座数量进行分析，以评估在哪个点上无法再正确识别模拟扩散个体。不出所料，扩散个体的正确识别情况因被选择“扩散”的个体、所使用的基因座数量、基因座的多态信息含量高低以及扩散个体被转移到的位置而有显著差异。对文献的回顾显示，迄今为止实施第一代迁徙者检测的研究平均使用了10个微卫星基因座。我们的结果表明，在此评估的研究系统中，至少需要27个基因座才能准确识别扩散个体。我们建议未来的研究采用我们所描述的方法，来确定在其研究系统中准确识别扩散个体所需的合适标记数量；自然系统的独特性质意味着每个研究系统所需的标记数量会有所不同。未来的研究可以对试点数据进行模拟扩散个体分析，以测试标记组合对当代扩散识别的稳健性，这为利用遗传数据估计扩散的研究的高效准确设计提供了一个强大工具。
