Leblois Raphael, Rousset François, Estoup Arnaud
Centre de Biologie et de Gestion des Populations, Campus International de Baillarguet CS 30 016, 34988 Montferrier sur Lez, France.
Genetics. 2004 Feb;166(2):1081-92. doi: 10.1534/genetics.166.2.1081.
Drift and migration disequilibrium are very common in animal and plant populations. Yet their impact on methods of estimation of demographic parameters was rarely evaluated especially in complex realistic population models. The effect of such disequilibria on the estimation of demographic parameters depends on the population model, the statistics, and the genetic markers used. Here we considered the estimation of the product Dsigma2 from individual microsatellite data, where D is the density of adults and sigma2 the average squared axial parent-offspring distance in a continuous population evolving under isolation by distance. A coalescence-based simulation algorithm was used to study the effect on Dsigma2 estimation of temporal and spatial fluctuations of demographic parameters. Estimation of present-time Dsigma2 values was found to be robust to temporal changes in dispersal, to density reduction, and to spatial expansions with constant density, even for relatively recent changes (i.e., a few tens of generations ago). By contrast, density increase in the recent past gave Dsigma2 estimations biased largely toward past demographic parameters values. The method was also robust to spatial heterogeneity in density and estimated local demographic parameters when the density is homogenous around the sampling area (e.g., on a surface that equals four times the sampling area). Hence, in the limit of the situations studied in this article, and with the exception of the case of density increase, temporal and spatial fluctuations of demographic parameters appear to have a limited influence on the estimation of local and present-time demographic parameters with the method studied.
漂变和迁移不平衡在动植物种群中非常普遍。然而,它们对人口统计学参数估计方法的影响很少得到评估,尤其是在复杂的现实种群模型中。这种不平衡对人口统计学参数估计的影响取决于种群模型、统计方法以及所使用的遗传标记。在这里,我们考虑了从个体微卫星数据估计乘积Dσ²,其中D是成年个体的密度,σ²是在距离隔离下演化的连续种群中亲代与子代轴向距离平方的平均值。基于合并的模拟算法被用来研究人口统计学参数的时间和空间波动对Dσ²估计的影响。研究发现,即使对于相对较近的变化(即几十代以前),当前Dσ²值的估计对于扩散的时间变化、密度降低以及密度不变的空间扩张都是稳健的。相比之下,近期的密度增加会使Dσ²估计值在很大程度上偏向过去的人口统计学参数值。当采样区域周围密度均匀(例如,在等于采样区域四倍的表面上)时,该方法对密度的空间异质性也很稳健,并且能够估计局部人口统计学参数。因此,在本文所研究的情况下,除了密度增加的情况外,人口统计学参数的时间和空间波动对所研究方法估计局部和当前人口统计学参数的影响似乎有限。