Theoretical Physics, School of Physics and Astronomy, The University of Manchester, M13 9PL, Manchester, United Kingdom.
Group of Nonlinear Physics, Faculty of Physics, University of Santiago de Compostela, E-15782, Santiago de Compostela, Spain.
Sci Rep. 2018 Mar 6;8(1):4068. doi: 10.1038/s41598-018-22062-w.
In evolutionary dynamics, the notion of a 'well-mixed' population is usually associated with all-to-all interactions at all times. This assumption simplifies the mathematics of evolutionary processes, and makes analytical solutions possible. At the same time the term 'well-mixed' suggests that this situation can be achieved by physically stirring the population. Using simulations of populations in chaotic flows, we show that in most cases this is not true: conventional well-mixed theories do not predict fixation probabilities correctly, regardless of how fast or thorough the stirring is. We propose a new analytical description in the fast-flow limit. This approach is valid for processes with global and local selection, and accurately predicts the suppression of selection as competition becomes more local. It provides a modelling tool for biological or social systems with individuals in motion.
在进化动力学中,“完全混合”种群的概念通常与任何时候的全对全相互作用相关联。这种假设简化了进化过程的数学运算,并使得解析解成为可能。同时,“完全混合”这个术语表明,通过物理搅拌种群可以实现这种情况。通过对混沌流中种群的模拟,我们表明,在大多数情况下,事实并非如此:无论搅拌速度有多快或多彻底,传统的完全混合理论都不能正确预测固定概率。我们在快速流动极限下提出了一个新的分析描述。这种方法适用于具有全局和局部选择的过程,并准确预测了随着竞争变得更加局部,选择的抑制。它为具有运动个体的生物或社会系统提供了一个建模工具。