Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy.
1] Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy [2] National Institute for Mathematical and Biological Synthesis (NIMBioS), University of Tennessee, Knoxville, TN, USA.
Heredity (Edinb). 2015 Sep;115(3):262-72. doi: 10.1038/hdy.2015.38. Epub 2015 Apr 29.
The introduction of invasive species to new locations (that is, biological invasions) can have major impact on biodiversity, agriculture and public health. As such, determining the routes and modality of introductions with genetic data has become a fundamental goal in molecular ecology. To assist with this goal, new statistical methods and frameworks have been developed, such as approximate Bayesian computation (ABC) for inferring invasion history. Here, we present a model of invasion accounting for multiple introductions from a single source (MISS), a heretofore largely unexplored model. We simulate microsatellite data to evaluate the power of ABC to distinguish between single and multiple introductions from the same source, under a range of demographic parameters. We also apply ABC to microsatellite data from three invasions of bumblebee in New Zealand. In addition, we assess the performance of several methods of summary statistics selection. Our simulated results suggested good ability to distinguish between one- and two-wave models over much but not all of the parameter space tested, independent of summary statistics used. Globally, parameter estimation was good except for bottleneck timing. For one of the bumblebee species, we clearly rejected the MISS model, while for the other two we found inconclusive results. Since a second wave may provide genetic reinforcement to initial colonists, help relieve inbreeding among founders, or increase the hazard of the invasion, its detection may be crucial for managing invasions; we suggest that the MISS model could be considered as a potential model in future theoretical and empirical studies of invasions.
引入新地点的入侵物种（即生物入侵）可能对生物多样性、农业和公共卫生产生重大影响。因此，利用遗传数据确定引入的途径和模式已成为分子生态学的基本目标。为此，已经开发了新的统计方法和框架，例如近似贝叶斯计算（ABC）来推断入侵历史。在这里，我们提出了一种考虑来自单一来源的多次引入的入侵模型（MISS），这是一个迄今为止尚未得到充分探索的模型。我们模拟了微卫星数据，以评估 ABC 在一系列人口参数下，从同一来源区分单次和多次引入的能力。我们还将 ABC 应用于新西兰三种熊蜂入侵的微卫星数据。此外，我们评估了几种汇总统计数据选择方法的性能。我们的模拟结果表明，在测试的大部分参数空间内，而不是所有参数空间内，都具有良好的能力来区分单波和两波模型，而与使用的汇总统计数据无关。总体而言，除了瓶颈时间外，参数估计都很好。对于一种熊蜂物种，我们明确拒绝了 MISS 模型，而对于另外两种，我们得出了不确定的结果。由于第二次浪潮可能会为初始殖民者提供遗传强化，帮助缓解创始人之间的近交，或增加入侵的危险，因此检测到它可能对管理入侵至关重要；我们建议在未来关于入侵的理论和实证研究中，可以考虑将 MISS 模型作为一种潜在的模型。
