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具有迁移的有限网络结构种群中的生态进化动力学

Eco-evolutionary dynamics in finite network-structured populations with migration.

作者信息

Pattni Karan, Ali Wajid, Broom Mark, Sharkey Kieran J

机构信息

Department of Mathematical Sciences, University of Liverpool, United Kingdom.

Department of Mathematical Sciences, University of Liverpool, United Kingdom.

出版信息

J Theor Biol. 2023 Sep 7;572:111587. doi: 10.1016/j.jtbi.2023.111587. Epub 2023 Jul 28.

Abstract

We consider the effect of network structure on the evolution of a population. Models of this kind typically consider a population of fixed size and distribution. Here we consider eco-evolutionary dynamics where population size and distribution can change through birth, death and migration, all of which are separate processes. This allows complex interaction and migration behaviours that are dependent on competition. For migration, we assume that the response of individuals to competition is governed by tolerance to their group members, such that less tolerant individuals are more likely to move away due to competition. We look at the success of a mutant in the rare mutation limit for the complete, cycle and star networks. Unlike models with fixed population size and distribution, the distribution of the individuals per site is explicitly modelled by considering the dynamics of the population. This in turn determines the mutant appearance distribution for each network. Where a mutant appears impacts its success as it determines the competition it faces. For low and high migration rates the complete and cycle networks have similar mutant appearance distributions resulting in similar success levels for an invading mutant. A higher migration rate in the star network is detrimental for mutant success because migration results in a crowded central site where a mutant is more likely to appear.

摘要

我们考虑网络结构对种群进化的影响。这类模型通常考虑固定规模和分布的种群。在此,我们考虑生态进化动力学,其中种群规模和分布可通过出生、死亡和迁移发生变化,所有这些都是独立的过程。这允许出现依赖于竞争的复杂相互作用和迁移行为。对于迁移,我们假设个体对竞争的反应受其对群体成员的容忍度支配,即容忍度较低的个体因竞争更有可能离开。我们研究在完全网络、循环网络和星型网络的稀有突变极限情况下突变体的成功情况。与具有固定种群规模和分布的模型不同,通过考虑种群动态明确地对每个位点的个体分布进行建模。这反过来又决定了每个网络的突变体出现分布。突变体出现的位置会影响其成功,因为这决定了它所面临的竞争。对于低迁移率和高迁移率,完全网络和循环网络具有相似的突变体出现分布,导致入侵突变体具有相似的成功水平。星型网络中较高的迁移率对突变体的成功不利,因为迁移会导致中心位点拥挤,突变体更有可能出现在那里。

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