合作与生态反馈补偿的进化动态。

IF 2 4区 生物学 Q2 BIOLOGY
Zi-Xuan Guo , Tian-Jiao Feng , Yi Tao , Rui-Wu Wang , Xiu-Deng Zheng
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引用次数: 0

摘要

我们建立了一个简单的理论模型(或一个示例)来说明合作的演化如何受到依赖密度的生存竞争的影响。在这个模型中,我们假设一个个体的生育力只取决于他与其他个体之间基于囚徒困境博弈的成对互动,而其生存力只与依赖密度的生存竞争力有关。我们的研究结果表明,如果合作者在生存能力上的优势能够补偿他们在生育力上付出的代价,那么不仅合作可以在进化上保持稳定,而且如果合作与叛逃都不能在进化上保持稳定,那么合作与叛逃的长期稳定共存也是可能的。此外,对于有限种群中的随机进化动态,我们的分析表明,合作者(或叛逃者)生存竞争力的提高(或降低)应有利于合作的进化出现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evolutionary dynamics of cooperation coupled with ecological feedback compensation

A simple theoretical model (or a demonstrative example) was developed to illustrate how the evolution of cooperation can be affected by the density-dependent survival competition, in which we assume that the fertility of an individual depends only on the pairwise interaction between him and other individuals based on Prisoner’s Dilemma game, while its viability is only related to the density-dependent survival competitiveness. Our results show that not only cooperation could be evolutionarily stable if the advantage of cooperators in viability can compensate for the cost they pay for their fertility, but also the long-term stable coexistence of cooperation and defection is possible if none of cooperation and defection is evolutionarily stable. Moreover, for the stochastic evolutionary dynamics in a finite population, our analysis shows that the increase (or decrease) of the survival competitiveness of cooperators (or defectors) should be conductive to the evolutionary emergence of cooperation.

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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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