当生物种群扩展到新领域时,进化结果会受到遗传漂移的强烈影响,等位基因频率的随机波动。同时,环境中的空间变异性也会显著影响争夺空间的亚群之间的竞争。关于这些内在和外在噪声源在种群动态中的相互作用知之甚少:环境异质性何时超过遗传漂移,反之亦然,他们的群体遗传学特征有什么区别?这里,在中性进化的背景下,我们研究了人口内在的相互作用,人口噪音和外在的,由异构环境提供的抑制随机噪声。使用多物种伊甸园模型,我们模拟一个种群在局部生长速率随机变化的景观上扩张,并测量这种变异性如何影响家谱树结构,从而遗传多样性。我们发现,对于强异质性,扩展前沿的基因组成在很大程度上是由一组最快的环境路径预先确定的。然后,这些最佳路径的与景观相关的统计信息取代了种群固有噪声的统计信息,成为进化动力学的主要决定因素。值得注意的是,家谱谱系合并的统计数据,从这些确定性路径中得出,在统一的景观中,仅从人口噪音中出现的统计数据就非常相似。这警告了对合并统计数据的解释,并为推断过去的人口动态提出了新的挑战。
When biological populations expand into new territory, the evolutionary outcomes can be strongly influenced by genetic drift, the random fluctuations in allele frequencies. Meanwhile, spatial variability in the environment can also significantly influence the competition between subpopulations vying for space. Little is known about the interplay of these intrinsic and extrinsic sources of noise in population dynamics: When does environmental heterogeneity dominate over genetic drift or vice versa, and what distinguishes their population genetics signatures? Here, in the context of neutral evolution, we examine the interplay between a population\'s intrinsic, demographic noise and an extrinsic, quenched random noise provided by a heterogeneous environment. Using a multispecies Eden model, we simulate a population expanding over a landscape with random variations in local growth rates and measure how this variability affects genealogical tree structure, and thus genetic diversity. We find that, for strong heterogeneity, the genetic makeup of the expansion front is to a great extent predetermined by the set of fastest paths through the environment. The landscape-dependent statistics of these optimal paths then supersede those of the population\'s intrinsic noise as the main determinant of evolutionary dynamics. Remarkably, the statistics for coalescence of genealogical lineages, derived from those deterministic paths, strongly resemble the statistics emerging from demographic noise alone in uniform landscapes. This cautions interpretations of coalescence statistics and raises new challenges for inferring past population dynamics.