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Modular knowledge systems accelerate human migration in asymmetric random environments

机译:模块化知识系统加速了非对称随机环境中的人类迁移

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摘要

Migration is a key mechanism for expansion of communities. In spatially heterogeneous environments, rapidly gaining knowledge about the local environment is key to the evolutionary success of a migrating population. For historical human migration, environmental heterogeneity was naturally asymmetric in the north–south (NS) and east–west (EW) directions. We here consider the human migration process in the Americas, modelled as random, asymmetric, modularly correlated environments. Knowledge about the environments determines the fitness of each individual. We present a phase diagram for asymmetry of migration as a function of carrying capacity and fitness threshold. We find that the speed of migration is proportional to the inverse complement of the spatial environmental gradient, and in particular, we find that NS migration rates are lower than EW migration rates when the environmental gradient is higher in the NS direction. Communication of knowledge between individuals can help to spread beneficial knowledge within the population. The speed of migration increases when communication transmits pieces of knowledge that contribute in a modular way to the fitness of individuals. The results for the dependence of migration rate on asymmetry and modularity are consistent with existing archaeological observations. The results for asymmetry of genetic divergence are consistent with patterns of human gene flow.
机译:迁移是扩展社区的关键机制。在空间异质环境中,迅速获得有关本地环境的知识是迁移人口进化成功的关键。对于历史上的人类迁徙,环境异质性在南北(NS)和东西向(EW)方向上自然是不对称的。我们在这里考虑在美洲的人口迁移过程,该过程建模为随机,不对称,模块化相关的环境。有关环境的知识决定了每个人的健康状况。我们提出了一个不对称的相图,作为承载能力和适应度阈值的函数。我们发现迁移速度与空间环境梯度的反补成正比,特别是当环境梯度在NS方向较高时,我们发现NS迁移率低于EW迁移率。个人之间的知识交流可以帮助在人群中传播有益的知识。当通信传递以模块化方式有助于个人适应性的知识时,迁移的速度就会提高。迁移率对不对称性和模块性的依赖性结果与现有的考古观察结果一致。遗传差异的不对称结果与人类基因流的模式一致。

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