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表型多样性与偶然合作的协同进化动态

Coevolutionary dynamics of phenotypic diversity and contingent cooperation.

作者信息

Wu Te, Wang Long, Fu Feng

机构信息

Center for Complex Systems, Xidian University, Xi'an, China.

Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.

出版信息

PLoS Comput Biol. 2017 Jan 31;13(1):e1005363. doi: 10.1371/journal.pcbi.1005363. eCollection 2017 Jan.

Abstract

Phenotypic diversity is considered beneficial to the evolution of contingent cooperation, in which cooperators channel their help preferentially towards others of similar phenotypes. However, it remains largely unclear how phenotypic variation arises in the first place and thus leads to the construction of phenotypic complexity. Here we propose a mathematical model to study the coevolutionary dynamics of phenotypic diversity and contingent cooperation. Unlike previous models, our model does not assume any prescribed level of phenotypic diversity, but rather lets it be an evolvable trait. Each individual expresses one phenotype at a time and only the phenotypes expressed are visible to others. Moreover, individuals can differ in their potential of phenotypic variation, which is characterized by the number of distinct phenotypes they can randomly switch to. Each individual incurs a cost proportional to the number of potentially expressible phenotypes so as to retain phenotypic variation and expression. Our results show that phenotypic diversity coevolves with contingent cooperation under a wide range of conditions and that there exists an optimal level of phenotypic diversity best promoting contingent cooperation. It pays for contingent cooperators to elevate their potential of phenotypic variation, thereby increasing their opportunities of establishing cooperation via novel phenotypes, as these new phenotypes serve as secret tags that are difficult for defector to discover and chase after. We also find that evolved high levels of phenotypic diversity can occasionally collapse due to the invasion of defector mutants, suggesting that cooperation and phenotypic diversity can mutually reinforce each other. Thus, our results provide new insights into better understanding the coevolution of cooperation and phenotypic diversity.

摘要

表型多样性被认为有利于偶然合作的进化,在这种合作中,合作者会优先向具有相似表型的其他个体提供帮助。然而,表型变异最初是如何产生并进而导致表型复杂性的构建,在很大程度上仍不清楚。在此,我们提出一个数学模型来研究表型多样性和偶然合作的共同进化动态。与之前的模型不同,我们的模型不假定任何规定的表型多样性水平,而是让其成为一个可进化的性状。每个个体一次只表达一种表型,并且只有所表达的表型对其他个体是可见的。此外,个体在表型变异潜力方面可能存在差异,这由它们可以随机切换到的不同表型的数量来表征。每个个体为保留表型变异和表达而承担与潜在可表达表型数量成比例的成本。我们的结果表明,在广泛的条件下表型多样性与偶然合作共同进化,并且存在一个最优的表型多样性水平最有利于促进偶然合作。对于偶然合作者来说,提高其表型变异潜力是值得的,从而增加通过新表型建立合作的机会,因为这些新表型可作为难以被背叛者发现和追踪的秘密标签。我们还发现,由于背叛者突变体的入侵,进化出的高水平表型多样性偶尔会崩溃,这表明合作和表型多样性可以相互促进。因此,我们的结果为更好地理解合作与表型多样性的共同进化提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb8b/5308777/a5494432de84/pcbi.1005363.g001.jpg

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